16 Vector Databases Jobs

Key Responsibilities: As an Infra AI Automation Programmer you will work on design development and deployment of AI systems that generate content or data often using techniques such as deep learning neural networks and generative models using Python backend coding Meet with clients in and remotely to understand their business objectives challenges and identify potential use cases for Generative AI Assess the client s existing technology infrastructure data landscape and AI maturity to determine the feasibility and best approaches for Gen AI adoption Conduct workshops and discovery sessions to brainstorm Gen AI applications across various business functions e g content creation customer service product development marketing Gen AI Strategy and Solution Design Develop tailored Gen AI strategies and roadmaps for clients in outlining specific use cases implementation plans and expected business outcomes Design Gen AI solutions architecture considering factors such as model selection e g large language models LLMs diffusion models data requirements integration with existing systems and scalability Evaluate and recommend appropriate Gen AI platforms tools and APIs e g OpenAI Google AI Azure AI open source libraries relevant to the client s needs and the Indian market Advise on prompt engineering techniques to optimize the output and performance of Gen AI models for specific client applications Technical Requirements: At least 2 years of programming experience in Python Handson experience in working on Gen AI Handson experience in Tensorflow Pytorch Langchain and Prompt Engineering Experience with vector databases and retrieval augmented generation RAG Familiarity with MLOps principles and tools for deploying and managing Gen AI models Understanding of ethical considerations and responsible AI frameworks Understanding of data structures data modelling SQL NOSQL Object oriented and functional programming GIT Knowledge of basic algorithms and object oriented and functional design principles Deep Knowledge of Mathematics Probability Statistics and Algorithms Good Communication skills Good analytical and problem solving skills Additional Responsibilities: Besides the professional qualifications of the candidates we place great importance in addition to various forms personality profile These include High analytical skills A high degree of initiative and flexibility High customer orientation High quality awareness Excellent verbal and written communication skills Preferred Skills: Technology->Machine Learning->Python,Technology->Machine Learning->TensorFlow,Technology->Machine Learning->Generative AI

Job Description: We are seeking a highly skilled and passionate AI/ML Engineer with strong expertise in Generative AI and Large Language Models (LLMs) . The ideal candidate will have hands-on experience in building, fine-tuning, and deploying agentic AI systems using modern GenAI frameworks. You will work on cutting-edge projects involving prompt engineering , RAG pipelines , and memory architectures such as vector databases. Responsibilities: Design and implement AI/ML solutions using modern LLM architectures and agentic AI concepts . Build and optimize intelligent agents using frameworks such as LangChain, AutoGen, CrewAI , or Semantic Kernel . Develop and fine-tune generative AI models with Transformers , HuggingFace , OpenAI API , etc. Implement and enhance Retrieval-Augmented Generation (RAG) pipelines and memory systems like vector databases (e.g., FAISS, Pinecone). Write high-performance Python code to support experimentation, model integration, and API interactions. Collaborate cross-functionally with product, design, and engineering teams in an agile development environment. Deploy AI solutions on cloud platforms (AWS, Azure, or GCP) with a focus on scalability and performance. Stay updated with the latest advancements in the AI/ML/GenAI space. Required Experience: 3 to 8 years of experience in AI/ML , with at least 1 year in Generative AI / LLM-based projects . Proven expertise in Python programming and related libraries for ML/GenAI. Hands-on experience with one or more GenAI frameworks (LangChain, AutoGen, etc.). Solid understanding of prompt engineering , RAG , vector DBs , and agent-based systems . Cloud deployment experience (AWS, Azure, or GCP) is a must. Strong analytical and problem-solving skills.

Ready to shape the future of work At Genpact, we don&rsquot just adapt to change&mdashwe drive it. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos AI Gigafactory, our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to agentic AI, our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that&rsquos shaping the future, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation, our teams implement data, technology, and AI to create tomorrow, today. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook. Inviting applications for the role of Senior Principal Consultant- Senior Data Engineer - Databricks, Azure & Mosaic AI Role Summary: We are seeking a Senior Data Engineer with extensive expertise in Data & Analytics platform modernization using Databricks, Azure, and Mosaic AI. This role will focus on designing and optimizing cloud-based data architectures, leveraging AI-driven automation to enhance data pipelines, governance, and processing at scale. Key Responsibilities: . Architect & modernize Data & Analytics platforms using Databricks on Azure. . Design and optimize Lakehouse architectures integrating Azure Data Lake, Databricks Delta Lake, and Synapse Analytics. . Implement Mosaic AI for AI-driven automation, predictive analytics, and intelligent data engineering solutions. . Lead the migration of legacy data platforms to a modern cloud-native Data & AI ecosystem. . Develop high-performance ETL pipelines, integrating Databricks with Azure services such as Data Factory, Synapse, and Purview. . Utilize MLflow & Mosaic AI for AI-enhanced data processing and decision-making. . Establish data governance, security, lineage tracking, and metadata management across modern data platforms. . Work collaboratively with business leaders, data scientists, and engineers to drive innovation. . Stay at the forefront of emerging trends in AI-powered data engineering and modernization strategies. Qualifications we seek in you! Minimum Qualifications . experience in Data Engineering, Cloud Platforms, and AI-driven automation. . Expertise in Databricks (Apache Spark, Delta Lake, MLflow) and Azure (Data Lake, Synapse, ADF, Purview). . Strong experience with Mosaic AI for AI-powered data engineering and automation. . Advanced proficiency in SQL, Python, and Scala for big data processing. . Experience in modernizing Data & Analytics platforms, migrating from on-prem to cloud. . Knowledge of Data Lineage, Observability, and AI-driven Data Governance frameworks. . Familiarity with Vector Databases & Retrieval-Augmented Generation (RAG) architectures for AI-powered data analytics. . Strong leadership, problem-solving, and stakeholder management skills. Preferred Skills: . Experience with Knowledge Graphs (Neo4J, TigerGraph) for data structuring. . Exposure to Kubernetes, Terraform, and CI/CD for scalable cloud deployments. . Background in streaming technologies (Kafka, Spark Streaming, Kinesis). Why join Genpact . Be a transformation leader - Work at the cutting edge of AI, automation, and digital innovation . Make an impact - Drive change for global enterprises and solve business challenges that matter . Accelerate your career - Get hands-on experience, mentorship, and continuous learning opportunities . Work with the best - Join 140,000+ bold thinkers and problem-solvers who push boundaries every day . Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

Data chunking, indexing pipelines - which includes working with Azure Form recognizer/ Llama , parse which can covert PDFs to markdowns. Working with vector Databases making indexes writing. Interested Candidates can contact: 7011567412.

Develop and deploy ML pipelines using MLOps tools, build FastAPI-based APIs, support LLMOps and real-time inferencing, collaborate with DS/DevOps teams, ensure performance and CI/CD compliance in AI infrastructure projects. Required Candidate profile Experienced Python developer with 4–8 years in MLOps, FastAPI, and AI/ML system deployment. Exposure to LLMOps, GenAI models, containerized environments, and strong collaboration across ML lifecycle

Job Description Join our team as a Generative AI Architect in the AI Practice! We are looking for a visionary individual to lead the design, development, and deployment of cutting-edge Generative AI solutions, driving business value across our products and services. Key Responsibilities: - Lead generative AI initiatives in text, ASR, TTS & STT generation and develop AI pipelines and ML models. - Design scalable AI systems using state-of-the-art generative models like LLMs and diffusion models. - Collaborate with cross-functional teams to integrate generative AI into business workflows. - Define best practices for model lifecycle management, focusing on data preparation, training, evaluation, deployment, and monitoring. - Guide ethical AI development with a focus on fairness, interpretability, and compliance. Qualifications: - Bachelors or Masters degree in Computer Science or related field. - 7+ years of AI/ML development experience, with 2+ years in generative AI. - Hands-on experience with large language models and diffusion models. - Strong proficiency in Python and ML frameworks. - Experience with Azure, GCP, and containerization. - Familiarity with AI architecture patterns and model fine-tuning. - Knowledge of data privacy laws and AI ethics principles. Preferred: - Experience deploying GenAI applications in production. - Knowledge of vector databases and retrieval-augmented generation. - Experience with CI/CD pipelines for ML. Skills : - Generative AI,Large Language Models (LLMs),Diffusion Models,Machine Learning (ML),Artificial Intelligence (AI),Natural Language Processing (NLP),Python Programming,ML Frameworks (e.g., TensorFlow, PyTorch, Hugging Face),Azure,GCP,Ethical AI,Responsible AI,Vector Databases, RAG

Job Overview : This is a Full-time role for a Generative AI Engineers for our client in Software Development, in Bangalore/Bengaluru, Karnataka. We are seeking a talented and experienced Generative AI Engineer to join our client team. The ideal candidate will have a strong background in artificial intelligence, machine learning, and programming with a focus on generative models. You will be responsible for designing, developing, and implementing cutting-edge generative AI solutions to solve complex problems and enhance our clients products and services. As part of a cross-functional engineer, you'll work closely with project managers, and DevOps professionals to enhance functionality, optimize workflows, and deliver high-quality Software. Success in this role is measured through key performance indicators (KPIs) such as System Performance, Code Quality, Team Effectiveness, Project Success. Role & responsibilities Design/develop multi-agent AI systems, architect RAG system/knowledge graphs Create proper engineering frameworks Build orchestration systems Implement generative AI techniques Collaborate on custom AI solutions Maintain scalable cloud AI Infrastructure Required Skills & Qualifications : Graduate/ Masters in Computer Science/AI related streams; model skills fine-tuning experience; multimodal AI knowledge; containerization/orchestration skills 3-5 years generative AI/LLM experience; expert Python skills; experience with LLM frameworks, multi-agent systems, vector databases; cloud proficiency (AWS, GCP, Azure) Compensation and Benefits: Base Salary: Competitive salary range based on experience and performance. Bonuses & Incentives: Performance-based bonuses. Health & Wellness: Comprehensive medical insurance. Career Growth: Ongoing training programs, professional development courses, mentorship opportunities, and career advancement prospects. Immediate joiner within 15 days 30 days notice period

Introduction Back-end developers are primarily responsible for the development of server-side software. The Backend developers help design, develop, and integrate solutions using best practice technologies, tools, techniques, and products our clients demand today. Whether you are working on projects internally or for a client, a backend developer is critical to the success of IBM and our clients worldwide. At IBM, you will use the latest software development tools, techniques and approaches and work with leading minds in the industry to build solutions you can be proud of. Your role and responsibilities As a Backend developer you will be responsible for Design, Development and testing of an IBM Cyber Resilience product through the full systems development lifecycle on both SaaS and Hybrid Cloud platforms. You will work in an agile, collaborative environment across software architecture, understanding both client-side development as well as the server-side development. We seek an applicant who will thrive in an open, dynamic, flexible, fun, spirited, collaborative environment an individual who desires creative freedom and the opportunity to work in a high performing team. Responsibilities: . Design/development/testing in programming languages like Java, python in Container environment. . Perform design and implementation reviews for other developers. . Participate in software design and code reviews to ensure a high level of software quality and also to share knowledge with the team members. . Work in a fast moving and forward-thinking development environment that is constantly researching and implementing using the latest technologies. . Participate in, and adhere to, professional software engineering practices using such tools and methodologies as Agile Software Development, Test Driven Development, Continuous Integration, Source Code Management (git), and GitHub. Ensure good code coverage. . Support bug fixes during development/testing and deploy to target environments. . Participate in the planning, creation and execution of automated test cases and load/performance testing. . Regularly develop automation testing and maintenance of microservices. . Create/maintain technical documentation. Hands on experience in handling and debugging customer issues, work with L2 support team. . Maintain a high level of proficiency with Computer Science/Software Engineering knowledge and contribute to the technical skills growth of other team members. ..Good team player. Required education Bachelors Degree Preferred education Masters Degree Required technical and professional expertise Atleast 10+ years of relevant Development experience Experience in working on a SaaS application with high industry standard CI/CD, and development cycle processes. Expertise in Core Java, Java J2EE, microservices architecture, Python. Experience in Building Restful API, SDK APIs using different frameworks. Expertise of database technologies such as mongoDB/SQL/NoSQL/Vector Databases. Good understanding of Docker, Kubernetes, OpenShift Container Platform, Ansible, Jenkins, Tekton. Experience in writing / executing Unit Tests and REST API automation. Experience and working knowledge of version Control systems like Github and build tools like Maven/Gradle. Continuous learning and ability to adapt to change. Strong sense of ownership of deliverables. Lead the team/component as required Architecture experience. Working across global teams and collaborating across teams and organization boundaries. Finding innovative ways to solve complex problems with cutting edge technologies.. Preferred technical and professional experience Experience working on Linux Experience in Backup/Data-protection, Storage products. Proficiency in cloud platforms - AWS and IBM Cloud. Experience in using messaging brokers like Kafka etc. Experience in Javascript, ReactJS, Typescript, HTML5, CSS. Good Knowledge of network fundamentals (TCP/IP, DNS, DHCP, VLANs, VPNs, routing, and subnetting etc) Understanding of Network security principles, including firewalls, encryption, identity and access management (IAM), and compliance standards. Understanding of VMware networking. Experience working with customers and/or customer facing teams. Excellent communication and presentation skills.

Design and implement RAG-based solutions to enhance LLM capabilities with external knowledge sources Develop and optimize LLM fine-tuning strategies for specific use cases and domain adaptation Create robust evaluation frameworks for measuring and improving model performance Build and maintain agentic workflows for autonomous AI systems Collaborate with cross-functional teams to identify opportunities and implement AI solutions Required Qualifications: Bachelor's or Master's degree in Computer Science, or related technical field 3+ years of experience in Machine Learning/AI engineering Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow) Practical experience with LLM deployments and fine-tuning Experience with vector databases and embedding models Familiarity with modern AI/ML infrastructure and cloud platforms (AWS, GCP, Azure) Strong understanding of RAG architectures and implementation Preferred Qualifications: Experience with popular LLM frameworks (Langchain, LlamaIndex, Transformers) Knowledge of prompt engineering and chain-of-thought techniques Experience with containerization and microservices architecture Background in NLP and deep learning Background in Reinforcement Learning Contributions to open-source AI projects Experience with ML ops and model deployment pipelines Skills and Competencies: Strong problem-solving and analytical skills Excellent communication and collaboration abilities Experience with agile development methodologies Ability to balance multiple projects and priorities Strong focus on code quality and best practices Understanding of AI ethics and responsible AI development

Job Description: Oracle Cloud Infrastructure (OCI) is a pioneering force in cloud technology, merging the agility of startups with the robustness of an enterprise software leader. Within OCI, the Oracle Generative AI Service team spearheads innovative solutions at the convergence of artificial intelligence and cloud infrastructure. As part of this team, you'll contribute to large-scale cloud solutions utilizing cutting-edge machine learning technologies, aimed at addressing complex global challenges. Join us to create innovative solutions using top-notch machine learning technologies to solve global challenges. We're looking for an experienced Principal Applied Data Scientist to join our OCI Gen-AI Solutions team for strategic customers. In this role, you'll collaborate with applied scientists and product managers to design, develop, and deploy tailored Gen-AI solutions with an emphasis on Large Language Models (LLMs), Agents, MPC and Retrieval Augmented Generation (RAG) with large OpenSearch clusters. As part of the OCI Gen AI and Data Solutions for strategic customers team, you will be responsible for developing innovative Gen AI and data services for our strategic customers.As a Principal Applied Data Scientist, you'll lead the development of advanced Gen AI solutions using the latest ML technologies combined with Oracle's cloud expertise. Your work will significantly impact sectors like financial services, telecom, healthcare, and code generation by creating distributed, scalable, high-performance solutions for strategic customers. Work directly with key customers and accompany them on their Gen AI journey - understanding their requirements, help them envision and design and build the right solutions and work together with their ML engineering to remove blockers. You will dive deep into model structure to optimize model performance and scalability. You will build state of art solutions with brand new technologies in this fast-evolving area. You will configure large scale OpenSearch clusters, setting up ingestion pipelines to get the data into the OpenSearch. You will diagnose, troubleshoot, and resolve issues in AI model training and serving. You may also perform other duties as assigned. Build re-usable solution patterns and reference solutions / showcases that can apply across multiple customers. Be an enthusiastic, self-motivated, and a great collaborator. Be our product evangelist - engage directly with customers and partners, participate and present in external events and conferences, etc. Qualifications and experience Bachelors or master's in computer science or equivalent technical field with 10+ years of experience Able to optimally communicate technical ideas verbally and in writing (technical proposals, design specs, architecture diagrams and presentations). Demonstrated experience in designing and implementing scalable AI models and solutions for production,relevant professional experience as end-to-end solutions engineer or architect (data engineering, data science and ML engineering is a plus), with evidence of close collaborations with PM and Dev teams. Experience with OpenSearch, Vector databases, PostgreSQL and Kafka Streaming. Practical experience with setting up and finetuning large OpenSearch Clusters. Experience in setting up data ingestion pipelines with OpenSearch. Experience with search algorithms, indexing, optimizing latency and response times. Practical experience with the latest technologies in LLM and generative AI, such as parameter-efficient fine-tuning, instruction fine-tuning, and advanced prompt engineering techniques like Tree-of-Thoughts. Familiarity with Agents and Agent frameworks and Model Predictive Control (MPC) Hands-on experience with emerging LLM frameworks and plugins, such as LangChain, LlamaIndex, VectorStores and Retrievers, LLM Cache, LLMOps (MLFlow), LMQL, Guidance, etc. Strong publication record, including as a lead author or reviewer, in top-tier journals or conferences. Ability and passion to mentor and develop junior machine learning engineers. Proficient in Python and shell scripting tools. Preferred Qualifications : Masters or Bachelor's in related field with 5+ years relevant experience Experience with RAG based solutions architecture. Familiarity in OpenSearch and Vector stores as a knowledge store Knowledge of LLM and experience delivering, Generative AI And Agent models are a significant plus. Familiarity and experience with the latest advancements in computer vision and multimodal modeling is a plus. Experience with semantic search, multi-modal search and conversational search. Experience in working on a public cloud environment, and in-depth knowledge of IaaS/PaaS industry and competitive capabilities.Experience with popular model training and serving frameworks like KServe, KubeFlow, Triton etc. Experience with LLM fine-tuning, especially the latest parameter efficient fine-tuning technologies and multi-task serving technologies. Deep technical understanding of Machine Learning, Deep Learning architectures like Transformers, training methods, and optimizers. Experience with deep learning frameworks (such as PyTorch, JAX, or TensorFlow) and deep learning architectures (especially Transformers). Experience in diagnosing, fixing, and resolving issues in AI model training and serving. Career Level - IC4

Job Description: We are seeking a highly skilled and passionate AI/ML Engineer with strong expertise in Generative AI and Large Language Models (LLMs) . The ideal candidate will have hands-on experience in building, fine-tuning, and deploying agentic AI systems using modern GenAI frameworks. You will work on cutting-edge projects involving prompt engineering , RAG pipelines , and memory architectures such as vector databases. Responsibilities: Design and implement AI/ML solutions using modern LLM architectures and agentic AI concepts . Build and optimize intelligent agents using frameworks such as LangChain, AutoGen, CrewAI , or Semantic Kernel . Develop and fine-tune generative AI models with Transformers , HuggingFace , OpenAI API , etc. Implement and enhance Retrieval-Augmented Generation (RAG) pipelines and memory systems like vector databases (e.g., FAISS, Pinecone). Write high-performance Python code to support experimentation, model integration, and API interactions. Collaborate cross-functionally with product, design, and engineering teams in an agile development environment. Deploy AI solutions on cloud platforms (AWS, Azure, or GCP) with a focus on scalability and performance. Stay updated with the latest advancements in the AI/ML/GenAI space. Required Experience: 3 to 8 years of experience in AI/ML , with at least 1 year in Generative AI / LLM-based projects . Proven expertise in Python programming and related libraries for ML/GenAI. Hands-on experience with one or more GenAI frameworks (LangChain, AutoGen, etc.). Solid understanding of prompt engineering , RAG , vector DBs , and agent-based systems . Cloud deployment experience (AWS, Azure, or GCP) is a must. Strong analytical and problem-solving skills.

Role Overview: As a Chief Technology Officer, you will craft the architecture and scalability roadmap for Lucios core services. Youll partner closely with the Founders, Product, and Engineering leadership to design and build systems that handle rapid growth, ensure high availability, and maintain data security. Youll also mentor senior engineers, shape best practices, and drive technical initiatives end-to-end. What Youll Do: Architect & Scale: Design and evolve Lucios microservices-based backend to support 10 user growth. Technical Leadership: Own end-to-end delivery of major features, from design through production rollout and monitoring. Mentorship: Guide and upskill engineers on system design, performance optimization, and code quality. Reliability & Security: Establish SLAs, implement observability (metrics, logging, tracing), and enforce best practices for data privacy and compliance. Cross-Functional Collaboration: Work with Founders, Product, and Design to translate lawyer workflows into robust, intuitive solutions. Hiring: Onboard talented engineers who are aligned with our vision and can help us scale. Who You Are 8+ years of software engineering experience, with 3+ years in a senior or staff role. Proven track record architecting and scaling cloud-native SaaS products (AWS/GCP/Azure). Deep expertise in backends, distributed data stores (MongoDB, Redis), and containerization (Docker, Kubernetes). Hands-on with DevOps toolchains (CI/CD, Terraform). Strong knowledge of LLM integrations, vector databases, and AI inference pipelines. Excellent communicator who can drive technical consensus and write clear design docs. Nice to Have Experience in legal-tech or document processing. Background in frontend frameworks (React) for end-to-end ownership.

Job Description AI Architect with at least 5 years of experience designing and deploying enterprise-grade AI/ML solutions , specializing in Databricks, MosaicML, and Large Language Models (LLMs ). Expertise in building scalable AI architectures that integrate deep learning, natural language processing (NLP), and MLOps best practices to enable real-time decision-making and predictive insights. Proven ability to collaborate with cross-functional teams to operationalize AI models while ensuring data security, scalability, and performance in cloud environments. Key Qualifications AI/ML Architecture & Deployment: Extensive experience in designing and deploying end-to-end AI pipelines using Databricks and MosaicML. Expertise in model training, fine-tuning, and inferencing of LLMs, ensuring optimal performance and cost-efficiency in production environments. Databricks Expertise: Strong hands-on experience with Databricks for data processing, model training, and model serving. Proficient in using Databricks Workflows, MLflow, Delta Lake, and advanced SQL/Scala/PySpark for building scalable AI pipelines. MosaicML Proficiency: Proven expertise in utilizing MosaicML for fine-tuning and training foundation models, leveraging model compression and distributed training techniques to reduce latency and enhance model performance. LLM & NLP Expertise: In-depth knowledge of Large Language Models (LLMs), including OpenAI, GPT models, BERT, LLaMA, and custom fine-tuning techniques. Experienced in building conversational AI, semantic search, text classification, and other NLP-based applications. Model Optimization & MLOps: Experience in implementing MLOps pipelines with tools like MLflow, Kubeflow, and Airflow to automate model training, versioning, deployment, and monitoring. Skilled in optimizing model inference with techniques such as quantization, pruning, and distributed inferencing. Data Pipeline & Feature Engineering: Expert in designing feature stores and scalable data pipelines using Apache Spark, Databricks Delta, and AWS Glue to facilitate efficient feature generation, model retraining, and data versioning. Cloud AI/ML Infrastructure: Proficiency in AWS, Azure, and GCP with expertise in setting up AI environments using EC2, S3, EKS, Lambda, and SageMaker. Ability to design fault-tolerant and highly available AI/ML infrastructure on cloud platforms. AI Governance & Security: Experience in implementing AI governance frameworks, ensuring compliance with AI ethics, bias mitigation, and explainability. Knowledge of data privacy, GDPR, and model interpretability in enterprise environments. Preferred Experience Experience with RAG (Retrieval Augmented Generation) pipelines and semantic search Familiarity with vector databases such as Pinecone, FAISS, and Weaviate Exposure to LangChain, Hugging Face, and OpenAI APIs Experience in building custom AI/LLM solutions tailored to enterprise use cases Technical Skills AI/ML Platforms: Databricks, MosaicML, SageMaker, Azure ML, GCP AI Programming & Frameworks: Python, PyTorch, TensorFlow, Hugging Face, PySpark, SQL MLOps & Orchestration: MLflow, Kubeflow, Airflow, Docker, Kubernetes, CI/CD LLM & NLP Models: GPT-3/4, BERT, LLaMA, Falcon, BLOOM, T5, LangChain Databricks Tools: Databricks SQL, Delta Lake, AutoML, Unity Catalog Cloud Platforms: AWS (S3, EC2, Lambda), Azure, GCP Version Control & Automation: Git, Jenkins, Terraform, CloudFormation Certifications (Preferred but not mandatory) Databricks Certified Professional Data Engineer/AI Engineer MosaicML Certification in Model Training & Optimization AWS Certified Machine Learning Specialty Microsoft Certified: Azure AI Engineer Associate

Job Description Cloud Architect Saama Technologies Key Responsibilities: Design and implement a robust and scalable cloud infrastructure to support the Graph RAG system. Optimize cloud resource utilization to achieve high performance while maintaining cost efficiency. Ensure adherence to security best practices and data governance compliance across the cloud environment. Select and implement appropriate Graph Database (e.g., Neo4j, AWS Neptune) and Vector Database (e.g., Weaviate, Pinecone, FAISS) solutions to meet scalability and efficiency requirements. Automate the provisioning and management of cloud infrastructure using Infrastructure as Code (IaC) tools. Required Skills: In-depth expertise in major cloud platforms (AWS, Azure, GCP). Strong knowledge of Graph Databases (Neo4j, AWS Neptune) and Vector Databases (Weaviate, Pinecone, FAISS). Extensive experience in designing and implementing cloud networking, security, and identity management solutions. Proficiency in containerization technologies (Docker) and container orchestration (Kubernetes). Strong knowledge of IaC tools (Terraform, CloudFormation). Deep understanding of DevOps principles and CI/CD practices. Additional Desired Skills: Experience with cloud cost optimization strategies. Familiarity with data security and compliance frameworks. Knowledge of cloud-native architectures and microservices. Experience with monitoring and logging tools for cloud environments.

Job Title: NLP Engineer Job Location: Chennai / Coimbatore Experience: 2+ years Job Type: Full-Time We are seeking an exceptional Senior NLP Engineer to join our cutting-edge AI/ML team. In this role, you will leverage your deep expertise in natural language processing, large language models, and retrieval-augmented generation to develop and optimize innovative NLP applications. Responsibilities: Design, develop, and deploy state-of-the-art NLP solutions utilizing LLMs and RAG architectures. Implement and optimize vector databases for efficient retrieval and augmentation of LLM-based systems. Collaborate with cross-functional teams to identify and address complex NLP challenges. Stay at the forefront of NLP research and apply latest techniques to enhance our AI/ML applications. Mentor junior engineers and contribute to the growth and knowledge sharing within the team. Requirements: Bachelor or Masters in Computer Science, NLP, ML or related field 2+ years of experience in developing NLP applications, (expertise in LLMs and RAG would be a plus) Strong understanding of transformer architectures, few-shot learning, and prompt engineering. Hands-on experience with NLP frameworks like Hugging Face, spaCy, NLTK, AllenNLP, etc. Proficiency in Python, PyTorch, TensorFlow and familiarity with C++/CUDA for optimization Experience with vector databases like Pinecone, Weaviate, Milvus for building RAG systems. Excellent problem-solving skills and ability to design efficient, scalable NLP pipelines. Strong communication skills and ability to collaborate in a fast-paced environment. Preferred Qualifications: Experience with deploying NLP models in production using AWS, GCP or Azure Knowledge of MLOps best practices and tools like MLflow, Kubeflow, AWS SageMaker If you are passionate about pushing the boundaries of NLP and developing game-changing AI applications, we would love to hear from you. Join our world-class team and help shape the future of intelligent systems.

What will you do: Consult on and enable successful execution of Data Science AI/ML and Generative AI solutions in assigned geo, focusing on Red Hat AI GTM. Educate customers and stakeholders on the value of Red Hat's Data Science AI/ML and Generative AI offerings, highlighting their applications and benefits. Lead and enable on hyper-competitive sales situations for the Data Science AI/ML and Generative AI portfolio, leveraging expertise in Predictive Analytics and Generative AI development practices. Serve as a geo-level bi-directional conduit of GTM for Red Hat AI between sales, products, engineering, marketing, enablement, and customer success, ensuring seamless communication and collaboration. Work closely with Red Hat AI product teams, providing feedback and identifying gaps in the offering to drive continuous improvement. Build lasting relationships with cloud providers and other 3rd parties for joint GTM, focusing on Data Science AI/ML and Generative AI solutions. Interface with regional sales leadership for account planning and GTM, ensuring alignment and effective execution of Red Hat AI sales strategies. What will you bring: 8+ years of Data Science and/or AI/ML application development practices and architectures. Subject matter expert in Data Science and Data Engineering concepts, Predictive Analytics, and/or Generative AI development practices Working knowledge of full stack AI development and deployment tools, including Feature Stores, Vector Databases, Embedding Models, ETL tooling, and modern programming languages/frameworks Experience with Kubernetes ecosystem, including competing technologies, and Cloud Service Providers with established account relationships Understanding of DevOps, agile, and similar concepts Working knowledge of full stack application development and deployment tools, including those of build, deployment, project management, automation, source code management, testing, quality/security, monitoring [APM], and configuration of the same, to deliver applications to production Executive presence with public speaking skills Expert Practitioner of the Challenger Sales Model Entrepreneurial mindset Preferred Qualifications Computer Science or other technical degree with an MBA, emphasizing a strong foundation in technical and business acumen. Previous experience as a sales engineer, technical sales, or similar role, highlighting expertise in driving sales and technical conversations in the Data Science AI/ML and Generative AI space. Experience working with cloud providers and other 3rd parties for joint GTM, leveraging relationships to drive indirect sales and co-selling opportunities. Background in leading development teams in delivering applications to production, consulting, and/or driving sales of Red Hat AI solutions, demonstrating a deep understanding of customer challenges and the ability to propose credible solutions. Strong relationships with Cloud Service Provider account teams, executives, and industry partners, with the ability to grow and maintain these relationships to drive co-selling and indirect sales opportunities. Technical and/or Sales role experience working directly for hyperscalers or in partner ecosystem