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5.0 - 7.0 years

0 Lacs

Gurugram, Haryana, India

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About Payoneer Founded in 2005, Payoneer is the global financial platform that removes friction from doing business across borders, with a mission to connect the world’s underserved businesses to a rising global economy. We’re a community with over 2,500 colleagues all over the world, working to serve customers, and partners in over 190 markets. By taking the complexity out of the financial workflows–including everything from global payments and compliance, to multi-currency and workforce management, to providing working capital and business intelligence–we give businesses the tools they need to work efficiently worldwide and grow with confidence. What will you do? �� Translate requirements and implement product features to perfection Work directly with developers as a team lead and manage products to conceptualise, build, test and realise products Deliver best-in-class code across a broad array of interactive web and mobile products Work on continuous improvement of the products through innovation and learning. A knack for benchmarking and optimization Developing features for highly complex, distributed transaction processing systems. Implement functionality for automated tests that will successfully pass and meet coding standards. Debug production issues and create subsequent mitigation plans. Optimize the performance of existing implementations. Stay abreast of new innovations and the latest technology trends and explore ways of leveraging these for improving the product in alignment with the business. What makes you a great match for us? �� 5-7 years of experience as a Backend developer. Experience in Node.JS & Nestjs is a must and experience in any of these is good to have - Javascript, Java, Typescript Database architecture and design on SQL (like Postgres) and NoSQL (like MongoDB systems. DOM manipulation and new CSS functionalities and processors Memory management, multithreaded programming and background processing. Unit-testing and a strong emphasis on TDD Debug moderately complex problems and analyze logs in production systems and to read existing code. Various data storage options, such as Relational, NoSQL Object-oriented design, data structures, and complexity analysis CI/CD environment with Jenkins/CircleCI Microservices Agile Development SCRUM methodology, JIRA Code versioning tools such as Git, Bitbucket, Mercurial, SVN, etc WebSocket, REDIS, Memcached, and Cloud Messaging Frameworks PUSH Notifications) Elasticsearch ELK stack- Elasticsearch, Kibana, and Logstash, REST API integration. Have the ability to deal with ambiguity Critical Thinker, Problem Solver and team player The Payoneer Ways of Working Act as our customer’s partner on the inside Learning what they need and creating what will help them go further. Continuously improve Always striving for a higher standard than our last. Do it. Own it. Being fearlessly accountable in everything we do. Build Each Other Up Helping each other grow, as professionals and people. If this sounds like a business, a community, and a mission you want to be part of, click now to apply. We are committed to providing a diverse and inclusive workplace. Payoneer is an equal opportunity employer, and all qualified applicants will receive consideration for employment no matter your race, color, ancestry, religion, sex, sexual orientation, gender identity, national origin, age, disability status, protected veteran status, or any other characteristic protected by law. If you require reasonable accommodation at any stage of the hiring process, please speak to the recruiter managing the role for any adjustments. Decisions about requests for reasonable accommodation are made on a case-by-case basis. Show more Show less

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7.0 - 9.0 years

0 Lacs

Gurugram, Haryana, India

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About Payoneer Founded in 2005, Payoneer is the global financial platform that removes friction from doing business across borders, with a mission to connect the world’s underserved businesses to a rising global economy. We’re a community with over 2,500 colleagues all over the world, working to serve customers, and partners in over 190 markets. By taking the complexity out of the financial workflows–including everything from global payments and compliance, to multi-currency and workforce management, to providing working capital and business intelligence–we give businesses the tools they need to work efficiently worldwide and grow with confidence. What will you do? Translate requirements and implement product features to perfection Work directly with developers as a team lead and manage products to conceptualise, build, test and realise products Deliver best-in-class code across a broad array of interactive web and mobile products Work on continuous improvement of the products through innovation and learning. A knack for benchmarking and optimization Developing features for highly complex, distributed transaction processing systems. Implement functionality for automated tests that will successfully pass and meet coding standards. Debug production issues and create subsequent mitigation plans. Optimize the performance of existing implementations. Stay abreast of new innovations and the latest technology trends and explore ways of leveraging these for improving the product in alignment with the business. What makes you a great match for us? 7-9 years of experience as a Backend developer Experience in Node.JS & Nestjs is a must and experience in any of these is good to have - Javascript, Java, Typescript Database architecture and design on SQL (like Postgres) and NoSQL (like MongoDB) systems DOM manipulation and new CSS functionalities and processors Memory management, multithreaded programming and background processing. Unit-testing and a strong emphasis on TDD Debug moderately complex problems and analyze logs in production systems and to read existing code. Various data storage options, such as Relational, NoSQL Object-oriented design, data structures, and complexity analysis CI/CD environment with Jenkins/CircleCI Microservices Agile Development (SCRUM methodology, JIR Code versioning tools such as Git, Bitbucket, Mercurial, SVN, etc WebSocket, REDIS, Memcached, and Cloud Messaging Frameworks (PUS Notifications) Elasticsearch ELK stack- Elasticsearch, Kibana, and Logstash, REST API integration. Have the ability to deal with ambiguity Critical Thinker, Problem Solver and team player The Payoneer Ways of Working Act as our customer’s partner on the inside Learning what they need and creating what will help them go further. Continuously improve Always striving for a higher standard than our last. Do it. Own it. Being fearlessly accountable in everything we do. Build Each Other Up Helping each other grow, as professionals and people. If this sounds like a business, a community, and a mission you want to be part of, click now to apply. We are committed to providing a diverse and inclusive workplace. Payoneer is an equal opportunity employer, and all qualified applicants will receive consideration for employment no matter your race, color, ancestry, religion, sex, sexual orientation, gender identity, national origin, age, disability status, protected veteran status, or any other characteristic protected by law. If you require reasonable accommodation at any stage of the hiring process, please speak to the recruiter managing the role for any adjustments. Decisions about requests for reasonable accommodation are made on a case-by-case basis. Show more Show less

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7.0 - 8.0 years

18 - 22 Lacs

Punjab

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Key Responsibilities Define and develop scalable, high-availability system architectures for enterprise applications. Break down functional requirements into technical components. Define data models and system interactions. Provide presentation to client on technical solutions to be implemented. Identify potential challenges and risks, along with mitigation strategies. Optimize backend and frontend components for low-latency, high-throughput performance. Develop strategies for efficient data processing, storage, and retrieval to handle large datasets. Identify and resolve bottlenecks in application logic, database queries, and API response times. Architect solutions that support multi-system integration, ensuring seamless data exchange. Implement high-performance caching strategies (Redis, Memcached) and database optimizations. Work closely with softwareengineers, DevOps teams, and business stakeholders to align technical solutions with business needs. Provide technical mentorship to developers and conduct code and architecture reviews. Define best practices and standards for software development, testing, and deployment. Required Skills & Qualifications Backend PHP -laravel, Node , Java , Python. Frontend : React.js, Angular. Databases : PostgreSQL, MySQL, MongoDB, Cassandra, Elasticsearch. Messaging & Streaming : Kafka, RabbitMQ, Pulsar. Cloud & DevOps : AWS (Lambda, S3, RDS), Kubernetes, Docker. Security & Compliance : OAuth 2.0, JWT, GDPR,. Experience In Building enterprise-grade, high-performance applications with large user bases. Designing microservices, event-driven architectures, and serverless solutions. Previously worked on similar enterprise products and experience in handling a team of 20 developers. Preferred Qualifications BTECH/BE is CSE from good tier college/university. Worked previously in similar role and have extensive experience working in complex products. Passionate about technology and innovation, continuously exploring new trends and contributing to the development of cutting-edge solutions.

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5.0 - 10.0 years

6 - 10 Lacs

Hyderabad

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What Were Looking For: As a Backend Engineer at Meltwater, you'll play a vital role in building cutting-edge social solutions for our global client base within the Explore mission We're seeking a proactive, quick-learning engineer who thrives in a collaborative environment Our culture values continuous learning, team autonomy, and a DevOps mindset Meltwater development teams take full ownership of their subsystems and infrastructure, including running on-call rotations With a heavy reliance on Azure services, Elasticsearch, Lambda, Terraform, and other technologies, we seek individuals with experience in search engines, big data analytics, infrastructure, systems engineering, and distributed systems. In this role, you'll have the opportunity to push the boundaries of our technology stack, from modifying open-source libraries to innovating with existing technologies If you're passionate about distributed systems at scale and finding new ways to extract insights from vast amounts of data, we invite you to join us in this exciting journey. What You'll Do: Analyze use cases, plan, and estimate work efforts. Design, develop, test, and maintain high-quality software components. Take full ownership of developed services within the team. Create robust, scalable, and maintainable software solutions using Java and related technologies. Collaborate closely with cross-functional teams to deliver software solutions that meet business requirements. Design efficient algorithms, data structures, and multithreaded applications for optimal performance. Participate actively in all phases of the software development lifecycle. Research and evaluate new technologies to enhance development processes and product capabilities. Troubleshoot and debug software issues, providing timely resolutions. Contribute to code reviews, architectural discussions, and technical documentation. What You'll Bring: Bachelor's or masters degree in Computer Science or a related field Minimum of 5 years of hands-on experience in software development using Node, Typescript, Azure Cloud. Proficiency in Functional Programming, encompassing data structures, algorithms, and multithreading. Proficiency in TypeScript features such as type definitions, decorators, generics, and async/await for building robust and scalable applications. Strong understanding of performance optimization, memory management, and CPU utilization. Experience with testing frameworks, particularly Jest, for ensuring code quality. Familiarity with dependency management tools. Familiarity with designing and maintaining microservices in a distributed architecture. Deployment expertise in cloud environments. Design and implementation proficiency in microservices architecture, including REST and Azure Function Apps. Knowledgeable about Azure, Kubernetes, and Docker for containerization and orchestration. Curiosity and a passion for learning new technologies and concepts. Enjoyment in collaborative problem-solving endeavours. Exceptional written and verbal communication skills in English. Openness to a hybrid work schedule, requiring one day per week in the office. Ability to collaborate with frontend developers, designers, and product managers to align technical solutions with business goals.

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25.0 years

0 Lacs

Gurugram, Haryana, India

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About the Job : Tower Research Capital is a leading quantitative trading firm founded in 1998. Tower has built its business on a high-performance platform and independent trading teams. We have a 25+ year track record of innovation and a reputation for discovering unique market opportunities. Tower is home to some of the world’s best systematic trading and engineering talent. We empower portfolio managers to build their teams and strategies independently while providing the economies of scale that come from a large, global organization. Engineers thrive at Tower while developing electronic trading infrastructure at a world class level. Our engineers solve challenging problems in the realms of low-latency programming, FPGA technology, hardware acceleration and machine learning. Our ongoing investment in top engineering talent and technology ensures our platform remains unmatched in terms of functionality, scalability and performance. At Tower, every employee plays a role in our success. Our Business Support teams are essential to building and maintaining the platform that powers everything we do — combining market access, data, compute, and research infrastructure with risk management, compliance, and a full suite of business services. Our Business Support teams enable our trading and engineering teams to perform at their best. At Tower, employees will find a stimulating, results-oriented environment where highly intelligent and motivated colleagues inspire each other to reach their greatest potential. Responsibilities: Supporting and maintaining the next-generation Post Trade systems at Tower Working with trade support and developers across multiple regions to resolve production issues Leading or contributing to migration, automation of support activities. Diagnosing and fixing bugs on existing production platforms Documenting production issues and production interventions taken Supporting new execution venues, trading products, and data vendors Establishing certification criteria for enhancements and/or new products to be released into production and integrating them into the testing and deployment process Working closely with end users to understand their needs and providing technical expertise Contributing to the design and implementation of the support system to enhance reliability and self-correction Monitoring and reporting on the status and health of production systems. Qualifications: 1- 5 years working in a fast-paced environment, including diagnosing and resolving production issues working for a global team At least 2 years' experience working with Enterprise applications written in Java, Python, Linux shell scripting, and job schedulers. Strong knowledge of Java/Python is a must. At least 2 years' experience working with SQL (ie. MySQL, PostGres) and NoSQL (ie. MongoDB, ElasticSearch) databases Past role(s) within electronic trading and a thorough understanding of financial instruments including equities, commodities, credit, interest rates, foreign exchange, cryptocurrencies, futures, forwards, and options will be a plus Strong problem-solving abilities Excellent written and oral communication skills Benefits: Tower’s headquarters are in the historic Equitable Building, right in the heart of NYC’s Financial District and our impact is global, with over a dozen offices around the world. At Tower, we believe work should be both challenging and enjoyable. That is why we foster a culture where smart, driven people thrive – without the egos. Our open concept workplace, casual dress code, and well-stocked kitchens reflect the value we place on a friendly, collaborative environment where everyone is respected, and great ideas win. Our benefits include: Generous paid time off policies Savings plans and other financial wellness tools available in each region Hybrid working opportunities Free breakfast, lunch and snacks daily In-office wellness experiences and reimbursement for select wellness expenses (e.g., gym, personal training and more) Volunteer opportunities and charitable giving Social events, happy hours, treats and celebrations throughout the year Workshops and continuous learning opportunities At Tower, you’ll find a collaborative and welcoming culture, a diverse team and a workplace that values both performance and enjoyment. No unnecessary hierarchy. No ego. Just great people doing great work – together. Tower Research Capital is an equal opportunity employer. Show more Show less

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7.0 years

0 Lacs

Sahibzada Ajit Singh Nagar, Punjab, India

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Everything we do is powered by our customers! Featured on Deloitte's Technology Fast 500 list and G2's leaderboard, Maropost offers a connected experience that our customers anticipate, transforming marketing, merchandising, and operations with commerce tools designed to scale with fast-growing businesses. With a relentless focus on our customers’ success, we are motivated by curiosity, creativity, and collaboration to power 5,000+ global brands. Driven by a customer-first mentality, we empower businesses to achieve their goals and grow alongside us. If you're ready to make a significant impact and be part of our transformative journey, Maropost is the place for you. Become a part of Maropost today and help shape the future of commerce! Roles & Responsibilities Build and manage a REST API stack for Maropost Web Apps. Given the architecture strategy related to our big data, analytics and cloud native product vision, work on the concrete architecture design and, when necessary, prototype it Understanding of systems architecture and ability to design scalable, performance-driven solutions. Drive innovation within the engineering team, identifying opportunities to improve processes, tools, and technologies Drive the architecture and design governance for systems and products under scope, as well as code and design reviews. Technical leadership of the development team and ensuring that they follow industry-standard best practices Evaluating and improving the tools and frameworks used in software development Design, develop and architect complex web applications Integrate with ML and NLP engines. DevOps, DBMS & Scaling on Azure or GCP. Skills & Qualifications B.E./B.Tech. Hands-on experience with tech stacks—RoR and PostgreSQL 7+ years of experience with building, including designing and architecting backend applications, web apps, and analytics, preferably in commerce cloud or marketing automation domains. Experience in deploying applications at scale in production systems. Experience with platform security capabilities (TLS, SSL etc.) Excellent track record in designing highly scalable big data/event-streaming/cloud architectures and experience with having put them in production. Advanced HLD, LLD, and Design Patterns knowledge is a must. Experience of high-performance web-scale & real-time response systems Knowledge of tenant data segregation techniques, such as schema-based multi-tenancy, database-per-tenant, and hybrid approaches, for ensuring data isolation and privacy. Knowledge of networking protocols, security standards, and best practices. Experience in building and managing API endpoints for multimodal clients. In-depth knowledge and hands-on experience in architecting and optimizing large-scale database clusters, specifically MySQL and PostgreSQL, for performance, scalability, and reliability. Proficiency in microservices architecture and containerization technologies (e.g., Docker, Kubernetes). Experience with DevOps practices and tools (e.g., CI/CD pipelines, infrastructure as code). Expertise in database design, including SQL and NoSQL databases, with a specific focus on MySQL and PostgreSQL Experience in implementing advanced indexing strategies, query optimization techniques, and database tuning methodologies for optimizing the performance of MySQL and PostgreSQL databases. Enthusiasm to learn and contribute to a challenging & fun-filled startup. A knack for problem-solving and following efficient coding practices. Very strong interpersonal communication and collaboration skills Advanced HLD, LLD, and Design Patterns knowledge is a must. Hands-on Experience (Advantageous) Proficiency in infrastructure-as-code tools such as Terraform or AWS CloudFormation. Experience with containerization technologies such as Docker and container orchestration platforms like Kubernetes. Proficiency in implementing advanced replication topologies, such as master-slave replication, multi-master replication, and synchronous replication, for MySQL and PostgreSQL databases. Knowledge of database partitioning techniques, such as range partitioning, hash partitioning, and list partitioning, for optimizing storage and query performance in large-scale database clusters. Familiarity with high-availability architectures, such as active-passive and active-active configurations, for ensuring continuous availability and reliability of MySQL and PostgreSQL databases. Familiarity with microservices architecture and related tools such as Istio, Envoy, or Linkerd. Knowledge of CI/CD pipelines and related tools such as Jenkins, GitLab CI/CD, or CircleCI. Experience with monitoring and observability tools such as Prometheus, Grafana, ELK stack (Elasticsearch, Logstash, Kibana), or Splunk. Familiarity with configuration management tools like Ansible, Puppet, or Chef. Proficiency in version control systems such as Git. Knowledge of scripting languages such as Bash, PowerShell, Ruby, or Python for automation tasks. Understanding of cloud-native security practices and tools such as Google Identity and Access Management (IAM), AWS Key Management Service (KMS), or Azure Active Directory. Familiarity with network security concepts such as VPNs, firewalls, and intrusion detection/prevention systems (IDS/IPS). What’s in it for you? You will have the autonomy to take ownership of your role and contribute to the growth and success of our brand. If you are driven to make an immediate impact, achieve results, thrive in a high performing team and want to grow in a dynamic and rewarding environment – You belong to Maropost! Show more Show less

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1.0 - 5.0 years

7 - 10 Lacs

Hyderabad

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What we are looking for: As a Content Platform Engineer at Meltwater, you'll play a vital role in building cutting-edge social solutions for our global client base within the Explore mission We're seeking a proactive, quick-learning engineer who thrives in a collaborative environment Our culture values continuous learning, team autonomy, and a DevOps mindset. Meltwater development teams take full ownership of their subsystems and infrastructure, including running on-call rotations With a heavy reliance on Java, Kotlin, AWS/Azure, GitHub Actions, Docker, Kubernetes, Terraform, Kafka/ SQS, PostgreSQL, ElasticSearch and other technologies, we seek individuals with experience in data curation, data management, and large-scale data processing You will be joining a team that maintains a multi-million entity knowledge graph that is used to support Meltwater's entity search and entity analytics at scale. In this role, you'll have the opportunity to push the boundaries of our technology stack, from modifying open-source libraries to innovating with existing technologies If you're passionate about large scale data management & curation and finding new ways to use knowledge graphs to extract insights from vast amounts of documents, we invite you to join us in this exciting journey. What You'll Bring: Bachelors or Masters degree in Computer Science or a related field. 24 years of working experience. At least 1+ years of experience in software development, especially with Java or Kotlin. Proficiency in SQL and experience working with large databases and complex datasets. Experience (1+ years) with Cloud infrastructure & Containerization, especially AWS/Azure. Experience with at least one of the following: oTerraform oGitHub Actions oDocker oKubernetes oKafka/SQS oOpenSearch Understanding or experience working with streaming pipelines and document processing on large-scale data management systems (e.g., PostgreSQL, Elasticsearch, Kafka/SQS). Nice-to-Have Skills Experience with Python. Experience with Benthos. Strong interest or experience in data quality and data curation (e.g., record linking, outlier detection, using LLMs for data curation). Familiarity with NLP techniques (e.g., named entity recognition, disambiguation, sentiment analysis). Demonstrated ability to quickly learn new tech stacks when needed (e.g., experience with other programming languages and frameworks). Strong communication skillsability to explain complex technical problems while balancing implementation details and high-level overviews. Front-end or Full-Stack experience is a plus (e.g., JavaScript, React, AWS Amplify).

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3.0 years

16 - 20 Lacs

Cuttack, Odisha, India

Remote

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Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

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3.0 years

16 - 20 Lacs

Bhubaneswar, Odisha, India

Remote

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Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

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3.0 years

16 - 20 Lacs

Kolkata, West Bengal, India

Remote

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Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Posted 3 weeks ago

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3.0 years

16 - 20 Lacs

Raipur, Chhattisgarh, India

Remote

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Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Posted 3 weeks ago

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3.0 years

16 - 20 Lacs

Guwahati, Assam, India

Remote

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Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Posted 3 weeks ago

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3.0 years

16 - 20 Lacs

Ranchi, Jharkhand, India

Remote

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Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Posted 3 weeks ago

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3.0 years

16 - 20 Lacs

Jamshedpur, Jharkhand, India

Remote

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Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Posted 3 weeks ago

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3.0 years

16 - 20 Lacs

Amritsar, Punjab, India

Remote

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Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

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12.0 years

0 Lacs

Hyderabad, Telangana, India

On-site

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Overview The Grafana and Elastic Architect will maintain and optimize the observability platform, ensure cost-effective operations, define guardrails, and promote best practices. This role will oversee the platform’s BAU support, manage vendors and partners, and collaborate closely with application owners to onboard applications. The Architect will also lead the deployment of AI Ops and other advanced features within Grafana and Elastic while working with other observability, ITSM, and platform architects. This position includes people management responsibilities and involves leading a team to achieve operational excellence. Responsibilities Key Responsibilities: Platform Ownership & Cost Optimization Maintain and enhance the Grafana and Elastic platforms to ensure high availability and performance. Implement cost control mechanisms to optimize resource utilization across Observability platforms. Establish platform guardrails, best practices, and governance models. BAU Support & Vendor/Partner Management Manage day-to-day operations, troubleshooting, and platform improvements. Engage and manage third-party vendors and partners to ensure SLA adherence and platform reliability. Work closely with procurement and finance teams to manage vendor contracts and renewals. Application Onboarding & Collaboration Partner with application owners and engineering teams to onboard applications onto the Observability platform. Define standardized onboarding frameworks and processes for application teams. Ensure seamless integration with existing observability solutions like AppDynamics, ServiceNow ITOM, and other monitoring tools. AI Ops & Advanced Features Implementation Deploy AI Ops capabilities within Grafana and Elastic to enhance proactive monitoring and anomaly detection. Implement automation and intelligent alerting to reduce MTTR and operational overhead. Stay updated with industry trends and recommend innovative AI-driven observability enhancements. Cross-Functional Collaboration Work closely with architects of AppDynamics, ServiceNow, and other Observability platforms to ensure an integrated monitoring strategy. Align with ITSM, DevOps, and Cloud teams to create a holistic observability roadmap. Lead knowledge-sharing sessions and create technical documentation for the team. People & Team Management Lead and managed a team responsible for Grafana and Elastic observability operations. Provide mentorship, coaching, and career development opportunities for team members. Define team goals, monitor performance, and drive continuous improvement in Observability practices. Foster a culture of collaboration, innovation, and accountability within the team. Qualifications Technical Expertise 12+ years of experience in IT Operations, Observability, or related fields. Strong expertise in Grafana and Elastic Stack (Elasticsearch, Logstash, Kibana). Experience in implementing AI Ops, machine learning, or automation within observability platforms. Proficiency in scripting and automation (Python, Ansible, Terraform) for Observability workloads. Hands-on experience with cloud-based Observability solutions, particularly in Azure environments. Familiarity with additional monitoring tools like AppDynamics, ServiceNow ITOM, SevOne, and ThousandEyes. Leadership & Collaboration Experience in managing vendors, contracts, and external partnerships. Strong stakeholder management skills and ability to work cross-functionally. Excellent communication and presentation skills. Ability to lead and mentor junior engineers in Observability best practices. Show more Show less

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3.0 years

16 - 20 Lacs

Kochi, Kerala, India

Remote

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Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

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3.0 years

16 - 20 Lacs

Indore, Madhya Pradesh, India

Remote

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Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

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3.0 years

16 - 20 Lacs

Greater Bhopal Area

Remote

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Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

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3.0 years

16 - 20 Lacs

Visakhapatnam, Andhra Pradesh, India

Remote

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Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Posted 3 weeks ago

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3.0 years

16 - 20 Lacs

Chandigarh, India

Remote

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Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Posted 3 weeks ago

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3.0 years

16 - 20 Lacs

Dehradun, Uttarakhand, India

Remote

Linkedin logo

Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Posted 3 weeks ago

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3.0 years

16 - 20 Lacs

Vijayawada, Andhra Pradesh, India

Remote

Linkedin logo

Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Posted 3 weeks ago

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3.0 years

16 - 20 Lacs

Mysore, Karnataka, India

Remote

Linkedin logo

Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Posted 3 weeks ago

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3.0 years

16 - 20 Lacs

Thiruvananthapuram, Kerala, India

Remote

Linkedin logo

Experience : 3.00 + years Salary : INR 1600000-2000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: SenseCloud) (*Note: This is a requirement for one of Uplers' client - A Seed-Funded B2B SaaS Company – Procurement Analytics) What do you need for this opportunity? Must have skills required: open-source, Palantir, privacy techniques, rag, Snowflake, LangChain, LLM, MLOps, AWS, Docker, Python A Seed-Funded B2B SaaS Company – Procurement Analytics is Looking for: Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders who’ve built things that actually work at scale. We’re not just rethinking how procurement analytics is done — we’re redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams’ attention, no more clunky dashboards —just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If you’re ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If you’re ready to help us build the future of procurement, analytics come join the ride. About The Role We’re looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problems—think automated research assistants, data-driven copilots, and workflow optimizers. You’ll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers’ ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 3–5 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iterate—without sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and work–life balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Posted 3 weeks ago

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Exploring Elasticsearch Jobs in India

Elasticsearch is a powerful search and analytics engine used by businesses worldwide to manage and analyze their data efficiently. In India, the demand for Elasticsearch professionals is on the rise, with many companies seeking skilled individuals to work on various projects involving data management, search capabilities, and more.

Top Hiring Locations in India

  1. Bangalore
  2. Pune
  3. Hyderabad
  4. Mumbai
  5. Delhi

These cities are known for their thriving tech industries and have a high demand for Elasticsearch professionals.

Average Salary Range

The salary range for Elasticsearch professionals in India varies based on experience and skill level. Entry-level positions can expect to earn around INR 4-6 lakhs per annum, while experienced professionals can earn upwards of INR 15 lakhs per annum.

Career Path

A typical career path in Elasticsearch may involve starting as a Junior Developer, moving on to become a Senior Developer, and eventually progressing to a Tech Lead position. With experience and expertise, one can also explore roles such as Solution Architect or Data Engineer.

Related Skills

Apart from Elasticsearch, professionals in this field are often expected to have knowledge of the following skills: - Apache Lucene - Java programming - Data modeling - RESTful APIs - Database management systems

Interview Questions

  • What is Elasticsearch and how does it differ from traditional databases? (basic)
  • Explain the purpose of an inverted index in Elasticsearch. (medium)
  • How does sharding work in Elasticsearch and why is it important? (medium)
  • What are the different types of queries supported by Elasticsearch? (basic)
  • How can you improve the performance of Elasticsearch queries? (medium)
  • What is the role of analyzers in Elasticsearch? (basic)
  • Explain the concept of mapping in Elasticsearch. (medium)
  • How does Elasticsearch handle scalability and high availability? (medium)
  • What is the significance of the "_source" field in Elasticsearch documents? (basic)
  • How does Elasticsearch handle full-text search? (medium)
  • What is the purpose of the "cluster" in Elasticsearch? (basic)
  • Explain the role of the "query DSL" in Elasticsearch. (medium)
  • How can you monitor the performance of an Elasticsearch cluster? (medium)
  • What are the different types of aggregations supported by Elasticsearch? (medium)
  • How does Elasticsearch handle document versioning? (medium)
  • What are the common data types supported by Elasticsearch? (basic)
  • How can you handle security in Elasticsearch? (medium)
  • Explain the concept of "indexing" in Elasticsearch. (basic)
  • What is the significance of the "refresh" interval in Elasticsearch? (basic)
  • How can you create a backup of an Elasticsearch cluster? (medium)
  • How does Elasticsearch handle conflicts during document updates? (medium)
  • Explain the concept of "relevance" in Elasticsearch search results. (medium)
  • How can you integrate Elasticsearch with other tools or platforms? (medium)
  • What are the key considerations for performance tuning in Elasticsearch? (advanced)

Closing Remark

As you explore job opportunities in Elasticsearch in India, remember to continuously enhance your skills and knowledge in this field. Prepare thoroughly for interviews and showcase your expertise confidently. With the right mindset and preparation, you can excel in your Elasticsearch career and contribute significantly to the tech industry in India. Good luck!

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