218 Rag Jobs - Page 4

Role & responsibilities We are looking for Gen AI Engineer position permanent position with US MNC for Bangalore/Chennai/Pune/Noida/Gurgaon location (Hybrid). Preferred candidate profile Experience Hands-on engineering role focused on designing, building, and deploying Generative AI and LLM-based solutions. The role requires deep technical proficiency in Python and modern LLM frameworks with the ability to contribute to roadmap development and cross-functional collaboration. Key Responsibilities: Design and develop GenAI/LLM-based systems using tools such as Langchain and Retrieval-Augmented Generation (RAG) pipelines. Implement prompt engineering techniques and agent-based frameworks to deliver intelligent, context-aware solutions. Collaborate with the engineering team to shape and drive the technical roadmap for LLM initiatives. Translate business needs into scalable, production-ready AI solutions. Work closely with business SMEs and data teams to ensure alignment of AI models with real-world use cases. Contribute to architecture discussions, code reviews, and performance optimization. Skills Required: Proficient in Python, Langchain, and SQL. Understanding of LLM internals, including prompt tuning, embeddings, vector databases, and agent workflows. Background in machine learning or software engineering with a focus on system-level thinking. Experience working with cloud platforms like AWS, Azure, or GCP. Ability to work independently while collaborating effectively across teams. Excellent communication and stakeholder management skills. Preferred Qualifications: Hands-on experience in LLMs and Generative AI techniques. Experience contributing to ML/AI product pipelines or end-to-end deployments. Familiarity with MLOps and scalable deployment patterns for AI models. Prior exposure to client-facing projects or cross-functional AI teams.

Role & responsibilities We are looking for Gen AI Engineer position permanent position with US MNC for Bangalore/Chennai/Pune/Noida/Gurgaon location (Hybrid). Preferred candidate profile Experience Hands-on engineering role focused on designing, building, and deploying Generative AI and LLM-based solutions. The role requires deep technical proficiency in Python and modern LLM frameworks with the ability to contribute to roadmap development and cross-functional collaboration. Key Responsibilities: Design and develop GenAI/LLM-based systems using tools such as Langchain and Retrieval-Augmented Generation (RAG) pipelines. Implement prompt engineering techniques and agent-based frameworks to deliver intelligent, context-aware solutions. Collaborate with the engineering team to shape and drive the technical roadmap for LLM initiatives. Translate business needs into scalable, production-ready AI solutions. Work closely with business SMEs and data teams to ensure alignment of AI models with real-world use cases. Contribute to architecture discussions, code reviews, and performance optimization. Skills Required: Proficient in Python, Langchain, and SQL. Understanding of LLM internals, including prompt tuning, embeddings, vector databases, and agent workflows. Background in machine learning or software engineering with a focus on system-level thinking. Experience working with cloud platforms like AWS, Azure, or GCP. Ability to work independently while collaborating effectively across teams. Excellent communication and stakeholder management skills. Preferred Qualifications: Hands-on experience in LLMs and Generative AI techniques. Experience contributing to ML/AI product pipelines or end-to-end deployments. Familiarity with MLOps and scalable deployment patterns for AI models. Prior exposure to client-facing projects or cross-functional AI teams.

Role & responsibilities We are looking for Gen AI Engineer position permanent position with US MNC for Bangalore/Chennai/Pune/Noida/Gurgaon location (Hybrid). Preferred candidate profile Experience Hands-on engineering role focused on designing, building, and deploying Generative AI and LLM-based solutions. The role requires deep technical proficiency in Python and modern LLM frameworks with the ability to contribute to roadmap development and cross-functional collaboration. Key Responsibilities: Design and develop GenAI/LLM-based systems using tools such as Langchain and Retrieval-Augmented Generation (RAG) pipelines. Implement prompt engineering techniques and agent-based frameworks to deliver intelligent, context-aware solutions. Collaborate with the engineering team to shape and drive the technical roadmap for LLM initiatives. Translate business needs into scalable, production-ready AI solutions. Work closely with business SMEs and data teams to ensure alignment of AI models with real-world use cases. Contribute to architecture discussions, code reviews, and performance optimization. Skills Required: Proficient in Python, Langchain, and SQL. Understanding of LLM internals, including prompt tuning, embeddings, vector databases, and agent workflows. Background in machine learning or software engineering with a focus on system-level thinking. Experience working with cloud platforms like AWS, Azure, or GCP. Ability to work independently while collaborating effectively across teams. Excellent communication and stakeholder management skills. Preferred Qualifications: Hands-on experience in LLMs and Generative AI techniques. Experience contributing to ML/AI product pipelines or end-to-end deployments. Familiarity with MLOps and scalable deployment patterns for AI models. Prior exposure to client-facing projects or cross-functional AI teams.

Role & responsibilities Lead the architecture and deployment of LLM and GenAI-based applications. Fine-tune and optimize state-of-the-art LLMs including GPT, LLaMA, Claude, Mistral, etc. Design and implement advanced prompt engineering and Retrieval-Augmented Generation (RAG) systems. Collaborate with data scientists, backend engineers, and product teams to deliver robust AIdriven solutions. Ensure security, performance, and cost optimization in model training and deployment. Translate complex business requirements into scalable GenAI solutions. Maintain best practices in code quality, version control, and documentation. Proven expertise in LLM fine-tuning, deployment, and inference workflows. Strong experience in Prompt Engineering and RAG (Retrieval-Augmented Generation) systems. Proficient in Python with hands-on experience in building AI pipelines. Demonstrated ability to lead system design and architecture for GenAI applications Preferred candidate profile Familiarity with GenAI toolkits such as LangChain, LlamaIndex, Haystack, or custom-built frameworks. Exposure to Microsoft Azure (preferred over AWS or GCP) for cloud deployments. Experience with scalable, secure AI infrastructure and CI/CD pipelines for ML models

AI/ML Architecture Development Implement and deploy machine learning models in production environments Work with generative AI models and NLP techniques (e.g., OpenAI, Claude APIs) Apply prompt engineering and retrieval-augmented generation (RAG) techniques Build end-to-end ML workflows from data preprocessing to model evaluation Contribute to the development of conversational AI solutions Software Engineering Data Pipeline Development Design, build, and maintain data pipelines and end-to-end ML workflows. Build and deploy web services that integrate ML models Implement APIs using frameworks like FastAPI or Flask Work with databases (preferably MySql) and data processing tools Ensure code quality, performance, and security in all implementations Deployment Integration Build production-grade ML models and APIs and deploy them on cloud platforms with the help of the DevOps team. Ability to Monitor, analyze, and optimize the performance of deployed models and data workflows with the help of Devops team Collaboration Work closely with cross-functional teams including data scientists and software engineers Contribute to a culture of learning and innovation Adapt to challenges even when requirements are ambiguous Technical Requirements: Programming Frameworks: Strong proficiency in Python with hands-on experience in TensorFlow, PyTorch, Keras, and related ML libraries/Ecosystem. Experience with data science tools (pandas, NumPymatplotlib, scikit-learn) Generative AI Expertise: Knowledge of generative AI models and frameworks, including OpenAI APIs, LangChain, LangGraph, Hugging Face Transformers, and related technologies. Experience in fine-tuning large language models (LLMs) and implementing RAG systems leveraging vector databases like Pinecone or similar. Experience in developing multi-agent Retrieval-Augmented Generation (RAG) applications, integrating automated workflows to streamline data retrieval,processing, and response generation. API Development: Experience in developing and deploying APIs using frameworks like FastAPI or Flask. Qualifications: Bachelor s degree in Computer Science, Engineering or related field. 5+ years of hands-on experience in AI/ML engineering, with expertise in generative AI and data engineering. Excellent problem-solving, analytical, and communication skills. Ability to work independently in a fast-paced, dynamic environment while effectively collaborating with cross-functional teams.

AI/ML Architecture Development Implement and deploy machine learning models in production environments Work with generative AI models and NLP techniques (e.g., OpenAI, Claude APIs) Apply prompt engineering and retrieval-augmented generation (RAG) techniques Build end-to-end ML workflows from data preprocessing to model evaluation Contribute to the development of conversational AI solutions Software Engineering Data Pipeline Development Design, build, and maintain data pipelines and end-to-end ML workflows. Build and deploy web services that integrate ML models Implement APIs using frameworks like FastAPI or Flask Work with databases (preferably MySql) and data processing tools Ensure code quality, performance, and security in all implementations Deployment Integration Build production-grade ML models and APIs and deploy them on cloud platforms with the help of the DevOps team. Ability to Monitor, analyze, and optimize the performance of deployed models and data workflows with the help of Devops team Collaboration Work closely with cross-functional teams including data scientists and software engineers Contribute to a culture of learning and innovation Adapt to challenges even when requirements are ambiguous Technical Requirements: Programming Frameworks: Strong proficiency in Python with hands-on experience in TensorFlow, PyTorch, Keras, and related ML libraries/Ecosystem. Experience with data science tools (pandas, NumPymatplotlib, scikit-learn) Generative AI Expertise: Knowledge of generative AI models and frameworks, including OpenAI APIs, LangChain, LangGraph, Hugging Face Transformers, and related technologies. Experience in fine-tuning large language models (LLMs) and implementing RAG systems leveraging vector databases like Pinecone or similar. Experience in developing multi-agent Retrieval-Augmented Generation (RAG) applications, integrating automated workflows to streamline data retrieval,processing, and response generation. API Development: Experience in developing and deploying APIs using frameworks like FastAPI or Flask. Qualifications: Bachelor s degree in Computer Science, Engineering or related field. 5+ years of hands-on experience in AI/ML engineering, with expertise in generative AI and data engineering. Excellent problem-solving, analytical, and communication skills. Ability to work independently in a fast-paced, dynamic environment while effectively collaborating with cross-functional teams.

RAG Pipeline Architectures Fine/Prompt/Instruction Tuning of LLMs machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn). data wrangling, data cleaning, data preprocessing, and data

In this role you will: Develop and fine-tune LLMs for contract analysis, regulatory classification, and risk assessment. Implement Retrieval-Augmented Generation (RAG) using vector embeddings and hybrid DB-based querying to power DPIA and compliance workflows. Build AI-driven contract analysis systems to detect dark patterns, classify clauses, and provide remediation suggestions. Develop knowledge graph-based purpose taxonomies for privacy policies and PII classification. Automate data discovery for structured and unstructured data, classifying it into PII categories. Optimize sliding window chunking, token-efficient parsing, and context-aware summarization for legal and compliance texts. Build APIs and ML services for deploying models in a high-availability production environment. Collaborate with privacy, legal, and compliance teams to build AI solutions that power Privy s data governance tools. Stay ahead of the curve with agentic RAG, multi-modal LLMs, and self-improving models in the compliance domain. Skills Required: LLM , RAG , AgenticAI , NLP , Python , Problem solving Candidate Attributes: Must-Have Skills 3-5 years of experience in Machine Learning, NLP, and LLM-based solutions. Strong expertise in fine-tuning and deploying LLMs (GPT-4, Llama, Mistral, or custom models). Experience with RAG-based architectures, including vector embeddings (FAISS, ChromaDB, Weaviate, Pinecone, or similar). Hands-on with agentic RAG, sliding window chunking, and efficient context retrieval techniques. Deep understanding of privacy AI use cases, including contract analysis, regulatory classification, and PII mapping. Proficiency in Python and frameworks like PyTorch, TensorFlow, JAX, Hugging Face, or LangChain. Experience in building scalable AI APIs and microservices. Exposure to MLOps practices, including model monitoring, inference optimization, and API scalability. Experience working with at least one cloud provider (AWS, GCP, or Azure). Good-to-Have Skills Experience in hybrid AI architectures combining vector search + relational databases. Familiarity with functional programming languages (Go, Elixir, Rust, etc.). Understanding of privacy compliance frameworks (DPDP Act, GDPR, CCPA, ISO 27701). Exposure to Kubernetes, Docker, and ML deployment best practices. Contributions to open-source LLM projects or privacy AI research.

Position Summary: As a member of Redaptive's AI team, you will be driving Agentic AI and Generative AI integration across all of Redaptives business units. You will drive AI development and integration across the organization, directly impacting Redaptives global sustainability efforts and shaping how we leverage AI to serve Fortune 500 clients. Responsibilities and Duties: Strategic Leadership (10%): Champion the AI/ML roadmap, driving strategic planning and execution for all initiatives. Provide guidance on data science projects (Agentic AI, Generative AI, and Machine Learning), aligning them with business objectives and best practices. Foster a data-driven culture, advocating for AI-powered solutions to business challenges and efficiency improvements. Collaborate with product management, engineering, and business stakeholders to identify opportunities and deliver impactful solutions Technical Leadership (40%): Architect and develop Proof-of-Concept (POC) solutions for Agentic AI, Generative AI, and ML. Utilize Python and relevant data science libraries, leveraging MLflow. Provide technical guidance on AI projects, ensuring alignment with business objectives and best practices. Assist in developmentand documentation of standards for ethical and regulatory-compliant AI usage. Stay current with AI advancements, contributing to the team's knowledge and expertise. Perform hands-on data wrangling and AI model development Operational Leadership (50%): Drive continuous improvement through Agentic AI, Generative AI, and predictive modeling. Participate in Agile development processes (Scrum and Kanban). Ensure compliance with regulatory and ethical AI standards. Other duties as assigned Required Abilities and Skills: Agentic AI development and deployment. Statistical modeling, machine learning algorithms, and data mining techniques. Databricks and MLflow for model training, deployment, and management on AWS. Working with large datasets on AWS and Databricks Strong hands-on experience with: Agentic AI development and deployment. Working with large datasets on AWS and Databricks. Desired Experience: Statistical modeling, machine learning algorithms, and data mining techniques. Databricks and MLflow for model training, deployment, and management on AWS. Experience integrating AI with IoT/event data. Experience with real-time and batch inference integration with SaaS applications. International team management experience. Track record of successful product launches in regulated environments Education and Experience: 5+ years of data science/AI experience Bachelor's degree in Statistics, Data Science, Computer Engineering, Mathematics, or a related field (Master's preferred). Proven track record of deploying successful Agentic AI, Generative AI, and ML projects from concept to production. Excellent communication skills, able to explain complex technical concepts to both technical and non-technical audiences.

Role & responsibilities Expertise in Data Analysis, Statistics, Computer Vision, AI & Machine Learning Concepts Unflinching zeal to learn, to try out Proof of Technology for new and emerging AI/ML Design and develop applications powered by Large Language Models (LLMs) like GPT-4, Claude, Gemini, and open-source models (LLaMA, Mistral, etc.) Implement RAG pipelines using LangChain and LangGraph for production-ready applications. Build and orchestrate autonomous and tool-using LLM agents. Integrate with vector databases (e.g., Pinecone, Chroma, Weaviate, FAISS) for semantic search and memory storage. Use tools like OpenAI Function Calling, React, or LangGraph Agents for decision-based workflows. Deploy applications using cloud platforms (Azure, AWS, GCP) with APIs, microservices, or serverless functions. Collaborate with product and design teams to develop chatbots, copilots, and multimodal interfaces. Monitor performance, cost, latency, and evaluate prompt effectiveness through prompt engineering best practices. Fine-tune, quantize, or use adapters (LoRA, PEFT) for open-source models where applicable. Stay up-to-date with the latest advancements in Gen AI, MLOps, and AI safety principles. Preferred candidate profile Bachelor's/Master's degree in Computer Science, Mathematics, Statistics, or a related field. 4-9 years of experience as a Data Scientist with strong skills in Python, NLP, Deep Learning, and Statistics. Hands-on experience with Generative AI, LangChain, LangGraph, and building LLM Agents for real-world AI applications. Strong Python skills with experience in deploying Gen AI apps using frameworks like FastAPI or Streamlit. Expertise in Retrieval-Augmented Generation (RAG) and working with vector databases like Pinecone, FAISS, or Chroma. Deep understanding of prompt engineering, OpenAI function calling, and chaining logic for dynamic interactions. Familiarity with cloud platforms such as Azure and AWS and deploying models to these platforms. Strong problem-solving and analytical skills with excellent communication and presentation skills. Disclaimer: The following job description serves as an informative reference for the tasks you may be required to perform. However, it does not constitute an integral component of your employment agreement and is subject to periodic modifications to align with evolving circumstances

AIML Engineer, NLP, LLM, AWS, RAG Systems

Role & responsibilities We are seeking a highly skilled and passionate GenAI & Data Science Engineer with 5-6 years of experience in Python development, Generative AI, and Data Science. The ideal candidate will have a strong background in AI agent workflows, LLM fine-tuning, and Retrieval-Augmented Generation (RAG) models. You will play a key role in designing, developing, and deploying cutting-edge AI solutions using frameworks such as Lang Chain, Llama Index, and Hugging Face. This role offers the opportunity to work on transformative AI-driven solutions, leveraging state-of-the-art tools and frameworks to create impactful solutions in real-world applications. Key Responsibilities: Design, develop, and deploy AI solutions with a focus on Generative AI and Data Science. Fine-tune Large Language Models (LLM) and implement Retrieval-Augmented Generation (RAG) models. Collaborate with cross-functional teams to integrate AI models into business workflows. Utilize frameworks such as Lang Chain, Llama Index, and Hugging Face to build scalable AI solutions. Participate in end-to-end AI model development, including data preprocessing, model selection, training, evaluation, and deployment. Continuously monitor and optimize the performance of AI models to ensure they meet business requirements. Work with stakeholders to understand AI requirements and contribute to solution design and architecture. Stay up to date with the latest advancements in AI technologies and industry trends Preferred candidate profile Qualifications Bachelors or Master’s degree in Computer Science, Data Science, AI, or a related field. 3-5 years of professional experience in Python development, AI, and Data Science. Proven experience with Generative AI, including fine-tuning LLMs and working with RAG models. Hands-on experience with frameworks like Lang Chain, Llama Index, and Hugging Face. Strong understanding of machine learning algorithms, deep learning, and natural language processing (NLP). Experience in AI model deployment and scaling in production environments. Technical Skills Programming: Python, including libraries like TensorFlow, PyTorch, Pandas, NumPy, etc. AI/ML Frameworks: Lang Chain, Llama Index, Hugging Face, etc. Machine Learning Algorithms: Supervised and Unsupervised Learning, NLP, Reinforcement Learning. Data Engineering: Data preprocessing, data wrangling, ETL processes. Cloud Platforms: AWS, GCP, Azure (experience with AI tools on cloud platforms). Version Control: Git, GitHub, GitLab. Familiarity with containerization tools like Docker and Kubernetes. Soft Skills Strong problem-solving skills and analytical thinking. Excellent communication and collaboration skills. Ability to work independently and as part of a team. Adaptability to evolving technologies and requirements. Strong attention to detail and high quality of work. Time management and ability to meet deadlines. Work Experience 3-5 years of experience working in AI, Data Science, or a related field. Practical experience in working with Generative AI, LLM fine-tuning, and RAG models. Experience with deployment of AI models in cloud environments. Proven track record delivering AI-driven solutions to solve real business problems. Good to Have Experience with other AI tools and frameworks like OpenAI GPT, DeepPavlov, or similar. Exposure to data integration and API development. Knowledge of advanced topics in NLP, such as transformers and attention mechanisms. Experience with building AI-powered applications or chatbots. Compensation & Benefits Salary: Competitive base salary based on experience and skills. Bonus: Annual performance-based bonus. Benefits: Health insurance, paid time off, work-from-home options, and retirement benefits. Learning & Development: Access to AI and Data Science training, conferences, and certifications. Key Performance Indicators (KPIs) & Key Result Areas (KRAs) KPIs: Timely delivery of AI projects and solutions. Quality and accuracy of fine-tuned AI models. Successful integration of AI solutions into business workflows. Continuous improvement in AI model performance (accuracy, speed, scalability). Stakeholder satisfaction and feedback on AI-driven solutions. Contribution to knowledge sharing and team collaboration. KRAs: AI model development, fine-tuning, and deployment. End-to-end ownership of AI solution delivery. Collaboration with cross-functional teams to define and implement business requirements. Optimization and monitoring of AI solutions in production environments.

Notice Period : Candidates with up to 1-month notice preferred Findability Sciences is looking for a hands-on AI expert with experience in developing and implementing comprehensive predictive and generative AI solutions. This is a core technical role rather than a support-based one. You will lead innovation and delivery across multiple industries. What we are looking for: 3+ years of experience in AI/ML with a Masters or Ph.D. in a relevant field Strong knowledge of Python, SQL, Machine Learning, LLMs, RAG, and Prompt Engineering Experience in predictive modeling, time series forecasting, and generative AI use cases Experience with ML Ops workflows model deployment, monitoring, versioning, and pipeline automation Key Responsibilities: Design and deploy predictive & GenAI solutions for real-world business use cases Build and optimize LLM-based workflows for summarization, retrieval, and Q&A Collaborate with cross-functional teams to define use cases and develop proof-of-concepts Translate business problems into ML/GenAI solutions and deliver outcomes Validate, compare, and optimize models for performance and scalability Apply basic ML Ops practices to ensure smooth deployment and monitoring of models Contribute to reusable pipelines, prompt tuning strategies, and production integration Present actionable insights and models to stakeholders clearly and effectively

Roles and Responsibilities : Must have skills: Python Programming, Machine Learning, Statistical Analysis, Data Science, Generative AI (GPT, DALLE, GANs), Cloud (AWS/Azure/GCP), Model Deployment, API Development, Docker/Kubernetes Good to have skills: PyTorch, TensorFlow, Large-Scale Data Processing, Cloud Integrations, NLP, Computer Vision, Security Best Practices, Performance Optimization, Open-Source Contributions Experience: Minimum 6-12+ years of experience in Data Science, Machine Learning, or related fields with a focus on Generative AI models (LLMs) and API development. Educational Qualification: Bachelor's or Master’s in Computer Science, Data Science, Statistics, Engineering, or related Analytics discipline from a premier institute. Job Summary: Accenture AI is seeking a talented and motivated Generative AI Data Scientist Analyst to join our Banking team. The ideal candidate will leverage their expertise in Generative AI models, Machine Learning, Data Analysis, and Cloud Platforms to develop innovative solutions and enhance AI capabilities. This role will involve collaborating with cross-functional teams to design, develop, and implement generative AI solutions that meet our business needs. Roles & Responsibilities: Collaboration: Work closely with product managers, engineers, and other stakeholders to understand requirements and deliver impactful AI solutions. Model Deployment: Containerize and deploy generative AI models using tools like Docker, Kubernetes, and cloud platforms (e.g., AWS, Azure, Google Cloud). API Development: Design, develop, and deploy robust APIs to expose generative AI models (e.g., GPT, DALLE, Stable Diffusion, GANs) for integration into client systems and applications. Client Collaboration: Work closely with clients to understand their technical requirements and deliver tailored API solutions that meet their business needs. Generative AI Model Integration: Integrate generative AI models into existing workflows, applications, and platforms via APIs. Performance Optimization: Optimize API performance for latency, scalability, and reliability, ensuring seamless user experiences. Data Pipeline Development: Build and maintain data pipelines to support real-time or batch processing for generative AI models. Security and Compliance: Implement security best practices and ensure APIs comply with data privacy and regulatory standards. Documentation: Create comprehensive API documentation, including usage examples, SDKs, and troubleshooting guides. Testing and Monitoring: Develop automated testing frameworks and monitoring systems to ensure API reliability and performance. Stay Updated: Keep up with the latest advancements in generative AI, API development, and cloud technologies to bring innovative solutions to clients. Professional & Technical Skills: Strong proficiency in Python programming and experience with machine learning frameworks (e.g., TensorFlow, PyTorch). Expertise in API Development and deployment, with hands-on experience with Docker, Kubernetes, and cloud platforms (AWS, GCP, Azure). Ability to build and optimize data pipelines for generative AI models. Knowledge of security best practices and ensuring compliance with regulatory standards. Strong problem-solving, analytical, and creative thinking skills to design and implement innovative solutions. Excellent communication skills, capable of conveying complex technical concepts to diverse audiences. Additional Information: Experience with large-scale data processing and expertise in NLP or computer vision. Contributions to open-source AI/ML projects. Experience with cloud integrations, big data technologies, and performance optimization. Familiarity with security standards and regulatory compliance in AI solutions

Job Description Technical Delivery Manager Saama Technologies Responsibilities: Oversee the end-to-end development and delivery of the Graph RAG system. Manage project timelines, ensuring timely delivery and adherence to milestones. Establish and maintain strong communication with client technical leads, providing regular updates and addressing technical concerns. Offer technical leadership and expertise in Graph Databases (e.g., Neo4j) and LLM-based applications. Collaborate with the team on architectural decisions, ensuring solutions are scalable, robust, and aligned with client requirements. Mitigate technical risks and address challenges proactively. Qualifications: Proven experience in technical project management and delivery, ideally within the AI/ML or data science domain. Strong understanding of Graph Databases and LLM-based systems. Experience with cloud-based development and deployment (AWS, GCP, or Azure). Excellent communication and interpersonal skills, with the ability to bridge the gap between technical and non-technical stakeholders. Ability to work independently and lead a team in a fast-paced environment. Experience with Agile methodologies. Required Skills: Knowledge of Graph Databases (Neo4) - Experience with LLM-based systems - Proficiency in LangChain - API development and cloud deployment expertise - Experience managing engineering teams and Agile methodologies Desired Skills: Familiarity with LangChain and API development. Knowledge of MLOps and CI/CD practices.

About the role PubMatic is seeking Data Analytics-focused Senior Software Engineers with expertise in building and optimizing AI agents, including strong skills in Hadoop, Spark, Scala, Kafka, Spark Streaming, and cloud-based solutions, with proficiency in programming languages such as Scala and Python. You will be responsible for developing advanced AI agents that enhance our data analytics capabilities, enabling our platform to handle complex information retrieval, contextual understanding, and adaptive interactions, ultimately improving our data-driven insights and analytical workflows. What You'll Do Build, design, and implement our highly scalable, fault-tolerant big data platform to process terabytes of data and provide customers with in-depth analytics. Develop backend services using Java, REST APIs, JDBC, and AWS. Build and maintain Big Data pipelines using technologies like Spark, Hadoop, Kafka, and Snowflake. Architect and implement real-time data processing workflows and automation frameworks. Design and develop GenAI-powered agents for analytics, operations, and data enrichment use cases using frameworks like LangChain, LlamaIndex, or custom orchestration systems. Integrate LLMs (e.g., OpenAI, Claude, Mistral) into existing services for query understanding, summarization, and decision support. Manage end-to-end GenAI workflows including prompt engineering, fine-tuning, vector embeddings, and retrieval-augmented generation (RAG). Working closely with cross-functional teams on improving the availability and scalability of large data platforms and the functionality of PubMatic software. Participate in Agile/Scrum processes such as sprint planning, sprint retrospective, backlog grooming, user story management, and work item prioritization. Frequently discuss with product managers about the software features to include in the PubMatic Data Analytics platform. Support customer issues over email or JIRA (bug tracking system), provide updates, and patches to customers to fix the issues. Perform code and design reviews for code implemented by peers or as per the code review process. We'd Love for You to Have Three to six years of coding experience in Java and backend development. Solid computer science fundamentals, including data structure and algorithm design, and creation of architectural specifications. Expertise in developing the Implementation of professional software engineering best practices for the full software development life cycle, including coding standards, code reviews. Hands-on experience with Big Data tools and systems like Scala Spark, Kafka, Hadoop, and Snowflake. Proven expertise in building GenAI applications, including: LLM integration (OpenAI, Anthropic, Cohere, etc.) LangChain, or similar agent orchestration libraries Prompt engineering, embeddings, and retrieval-based generation (RAG) Experience in developing and deploying scalable, production-grade AI or data systems. Ability to lead end-to-end feature development and debug distributed systems. Experience in developing and delivering large-scale big data pipelines, real-time systems & data warehouses would be preferred. Demonstrated ability to achieve stretch goals in a very innovative and fast-paced environment. Demonstrated ability to learn new technologies quickly and independently. Excellent verbal and written communication skills, especially in technical communications. Strong interpersonal skills and a desire to work collaboratively. Qualifications Should have a bachelor's degree in engineering (CS / IT) or equivalent degree from a well-known institute/university. Apply to the link below: https://pubmatic.com/job/?gh_jid=4692032008

Technical Architect - GenAI Job Responsibilities Excellent communication skills and customer management skills 12+ years of deep technical expertise in distributed transactional scale & digital architectures. Experience in Solution Architecture Experience in Java or .NET and related frameworks Experience in GenAI, ChatGPT, LLM, RAG architectures Experience in CoPilot etc Experience in Cloud solutions. Either AWS or Azure or GCP Experience in Microservices and cloud native architectures Role Purpose The purpose of the role is to create exceptional architectural solution design and thought leadership and enable delivery teams to provide exceptional client engagement and satisfaction. Develop architectural solutions for the new deals/ major change requests in existing deals Creates an enterprise-wide architecture that ensures systems are scalable, reliable, and manageable. Provide solutioning of RFPs received from clients and ensure overall design assurance Develop a direction to manage the portfolio of to-be-solutions including systems, shared infrastructure services, applications in order to better match business outcome objectives Analyse technology environment, enterprise specifics, client requirements to set a collaboration solution design framework/ architecture Provide technical leadership to the design, development and implementation of custom solutions through thoughtful use of modern technology Define and understand current state solutions and identify improvements, options & tradeoffs to define target state solutions Clearly articulate, document and sell architectural targets, recommendations and reusable patterns and accordingly propose investment roadmaps Evaluate and recommend solutions to integrate with overall technology ecosystem Works closely with various IT groups to transition tasks, ensure performance and manage issues through to resolution Perform detailed documentation (App view, multiple sections & views) of the architectural design and solution mentioning all the artefacts in detail Validate the solution/ prototype from technology, cost structure and customer differentiation point of view Identify problem areas and perform root cause analysis of architectural design and solutions and provide relevant solutions to the problem Collaborating with sales, program/project, consulting teams to reconcile solutions to architecture Tracks industry and application trends and relates these to planning current and future IT needs Provides technical and strategic input during the project planning phase in the form of technical architectural designs and recommendations Collaborates with all relevant parties in order to review the objectives and constraints of solutions and determine conformance with the Enterprise Architecture. Identifies implementation risks and potential impacts. Enable Delivery Teams by providing optimal delivery solutions/ frameworks Build and maintain relationships with executives, technical leaders, product owners, peer architects and other stakeholders to become a trusted advisor Develops and establishes relevant technical, business process and overall support metrics (KPI/SLA) to drive results Manages multiple projects and accurately reports the status of all major assignments while adhering to all project management standards Identify technical, process, structural risks and prepare a risk mitigation plan for all the projects Ensure quality assurance of all the architecture or design decisions and provides technical mitigation support to the delivery teams Recommend tools for reuse, automation for improved productivity and reduced cycle times Leads the development and maintenance of enterprise framework and related artefacts Develops trust and builds effective working relationships through respectful, collaborative engagement across individual product teams Ensures architecture principles and standards are consistently applied to all the projects Ensure optimal Client Engagement Support pre-sales team while presenting the entire solution design and its principles to the client Negotiate, manage and coordinate with the client teams to ensure all requirements are met and create an impact of solution proposed Demonstrate thought leadership with strong technical capability in front of the client to win the confidence and act as a trusted advisor Competency Building and Branding Ensure completion of necessary trainings and certifications Develop Proof of Concepts (POCs),case studies, demos etc. for new growth areas based on market and customer research Develop and present a point of view of Wipro on solution design and architect by writing white papers, blogs etc. Attain market referencability and recognition through highest analyst rankings, client testimonials and partner credits Be the voice of Wipros Thought Leadership by speaking in forums (internal and external) Mentor developers, designers and Junior architects in the project for their further career development and enhancement Contribute to the architecture practice by conducting selection interviews etc Team Management Resourcing Anticipating new talent requirements as per the market/ industry trends or client requirements Hire adequate and right resources for the team Talent Management Ensure adequate onboarding and training for the team members to enhance capability & effectiveness Build an internal talent pool and ensure their career progression within the organization Manage team attrition Drive diversity in leadership positions Performance Management Set goals for the team, conduct timely performance reviews and provide constructive feedback to own direct reports Ensure that the Performance Nxt is followed for the entire team Employee Satisfaction and Engagement Lead and drive engagement initiatives for the team Track team satisfaction scores and identify initiatives to build engagement within the team Stakeholder Interaction Stakeholder Type Stakeholder Identification Purpose of Interaction Internal Delivery teamsReview of architectural process deployment in engagements, escalation management, issue resolution Pre-sales teamFor solutioning and architectural design purposePractice teamsTo understand the different solution portfoliosHolmes engineering and roll outFor automation purposeTalent Transformation Team, Competency GroupPlan and support delivery of Technical Trainings, knowledge sharing HRBPFor hiring and managing resourcesFinanceRevenue / budgetsTalent acquisition teamRecruitment External Vendors/ PartnersFor strategic alignment and partnerships, training Industry forums Best practices, market intelligence, knowledge sharing Display Lists the competencies required to perform this role effectively Functional Competencies/ Skill Domain/Industry Knowledge - Awareness and knowledge of broad economic, demographic, technological and global trends within own ecosystem - Expert Market Intelligence - Deep specialized understanding of the ecosystem practice, overall market & competition and nuances of delivery in that domain - Master Systems Thinking - Understanding of the Wipro system (interrelatedness, interdependencies and boundaries) and perform problem solving in a complex environment - Expert Leveraging Technology - In-depth knowledge of and mastery over ecosystem technology that commands expert authority respect - Master Asset reusability - ability to re-use the assets to ensure scalability and optimization - Expert Technical knowledge - architecture design principles, framework and documentation - Expert Competency Levels Foundation Knowledgeable about the competency requirements. Demonstrates (in parts) frequently with minimal support and guidance. Competent Consistently demonstrates the full range of the competency without guidance. Extends the competency to difficult and unknown situations as well. Expert Applies the competency in all situations and is serves as a guide to others as well. Master Coaches others and builds organizational capability in the competency area. Serves as a key resource for that competency and is recognised within the entire organization. Behavioral Competencies Strategic perspective Technology Acumen Innovation Managing Complexity Client centricity Execution excellence Change agility Passion for results Nurturing people Executive presence Deliver No. Performance Parameter Measure 1. Support sales team to create wins % of proposals with Quality Index >7, timely support of the proposals, identifying opportunities/ leads to sell services within/ outside account (lead generation), no. of proposals led 2. Delivery support CSAT, delivery as per cost, quality and timelines, Identify and develop resuable components, utilization %, Recommend tools for reuse, automation for improved productivity and reduced cycle times 3. Capability development % trainings and certifications completed, increase in ACE certifications, thought leadership content developed (white papers, Wipro PoVs) 4. Team Management Team attrition %, Employee satisfaction score

Hiring an AI-focused developer with expertise in Node.js, API integration (Azure OpenAI, RAG, parameter tuning), and AI pipeline optimization. Bonus: MCP knowledge & experience with image analysis. AI Developer Required Candidate profile AI Developer with 2+ years' experience in Node.js, Azure OpenAI, RAG, API integration, and AI pipelines. Bonus: MCP knowledge & image analysis (OpenAI/Anthropic).

Job Title: AI Developer Supply Chain Management Location: Permanent Remote Job Type: Full-time Team: Product AI Engineering We are looking for a talented LLM Developer to join our AI Engineering team and contribute to the development of the SCM Expert AI Agent the core brain behind AI capabilities like demand forecasting, anomaly detection, ETA prediction, and route optimization in the FarmToPlate (F2P) platform. In this role, you will focus on integrating and optimizing LLM-based agentic architectures using frameworks like LangChain, CrewAI, and RAG pipelines. Youll work closely with traditional ML developers and backend engineers to deploy intelligent, explainable, and real-time decision agents for supply chain management. Responsibilities: Design, build, and optimize LLM-based agents using LangChain, CrewAI, or custom wrappers. Implement RAG pipelines with vector stores (e.g., FAISS, ChromaDB) and embedding models. Develop LLM-powered tools for demand forecasting, query understanding, anomaly explanations, and summarization. Integrate agents with internal and external data sources using tools like MongoDB, Sklearn datasets, or Browsing Agents. Implement prompt engineering, agent memory, and context-chaining for more dynamic agent behavior. Collaborate with data science and product teams to translate SCM logic into agentic workflows. Expose models and agents through APIs using FastAPI, including role-based access if needed. Optimize runtime performance with quantization, PEFT (parameter-efficient finetuning), and model caching. Track experiments, versions, and deployment artifacts using tools like MLflow, SageMaker, or custom registries. Requirements: 3-5 years of experience working on Python-based AI systems. Strong understanding of LLMs, Transformers, Prompt Engineering, and conversational AI. Hands-on experience with LangChain, CrewAI, OpenAI/GPT APIs, or Hugging Face Transformers. Familiarity with RAG concepts, vector databases (FAISS, Chroma), and embedding techniques. Good knowledge of API frameworks (FastAPI/Flask) and working with JSON schema-driven inputs. Basic understanding of traditional ML models and workflows (e.g., regression, classification, anomaly detection). Comfortable integrating external data tools and APIs into LLM pipelines. Bonus Points For Experience building Agentic RAG systems that combine logic, tools, memory, and models. Knowledge of Open Source LLM tuning using PEFT, LoRA, bitsandbytes, Unsloth, etc. Familiarity with SageMaker, EKS, or deploying custom models to the cloud. Experience in supply chain/logistics, or working with ERP/SCM structured data. Built monitoring dashboards using Evidently.ai or similar model observability tools. Why Join Us Be part of a domain-driven AI platform blending supply chain expertise with modern agentic LLM architectures. Work on real-world use cases that impact farm-to-plate food systems at scale. Collaborate with a fast-moving, cross-functional team that values innovation, ownership, and outcome. Learn and grow in a modular, full-stack AI environment where your ideas become deployed APIs. Enjoy flexibility in remote, experimentation, and continuous learning.

Job Description Requirement Name / Title GenAI Developer Work Location Chennai/ Bangalore/Pune/Kolkata Shift General Shift Mandatory Skills Gen AI, LLM, RAG, Lang chain, Mistral,Llama, Vector DB, Azure/GCP/ Lambda, Python, Tensorflow, Pytorch Preferred Skills GPT-4, NumPy, Pandas, Keras, Databricks, Pinecone/Chroma/Weaviate, Scale/Labelbox, Job Description / Roles & Responsibilities (in Detail) We are looking for a good Python Developer with Knowledge of Machine learning and deep learning framework. • Take care of entire prompt life cycle like prompt design, prompt template creation, prompt tuning/optimization for various GenAI base models • Design and develop prompts suiting project needs • Stakeholder management across business and domains as required for the projects • Evaluating base models and benchmarking performance • Implement prompt guardrails to prevent attacks like prompt injection, jailbreaking and prompt leaking • Develop, deploy and maintain auto prompt solutions • Design and implement minimum design standards for every use case involving prompt engineering • You will be responsible for training the machine learning and deep learning model. • Writing reusable, testable, and efficient code using Python • Design and implementation of low-latency, high-availability, and performant applications • Implementation of security and data protection • Integration of data storage solutions and API Gateways • Production change deployment and related support If you're interested or know someone who fits this role, feel free to reach out. WhatsApp: 9871530393 Email: shweta.gupta@sspearhead.com Warm Regards SHWETA GUPTA || Senior Recruitment Specialist Spearhead Professional Services Call/ WhatsApp: 9871530393 LinkedIn Profile: shwetagupta1810

About the Role We are looking for an experienced and visionary Generative AI Architect with 8-12 years of experience in AI/ML, including hands-on work with LLMs (Large Language Models) and Generative AI solutions . In this strategic technical leadership role, you will be responsible for designing and overseeing the development of advanced GenAI platforms and solutions that transform business operations and customer experiences. As the GenAI Architect, you will work closely with data scientists, ML engineers, product teams, and stakeholders to conceptualize, prototype, and scale generative AI use cases across the organization or client engagements. Key Responsibilities GenAI Solution Architecture & Design Lead the design and development of scalable GenAI solutions leveraging LLMs , diffusion models , and multimodal architectures . Architect end-to-end pipelines involving prompt engineering , vector databases , retrieval-augmented generation (RAG) , and LLM fine-tuning . Select and integrate foundational models (e.g., GPT, Claude, LLaMA, Mistral ) based on business needs and technical constraints. Technical Strategy & Leadership Define GenAI architecture blueprints, best practices, and reusable components for rapid development and experimentation. Guide teams on model evaluation, inference optimization , and cost-effective scaling strategies . Stay current on the rapidly evolving GenAI landscape and assess emerging tools, APIs, and frameworks. Collaboration & Delivery Work with product owners, business leaders, and data teams to identify high-impact GenAI use cases across domains like customer support, content generation, document understanding, and code generation. Support PoCs, pilots, and production deployments of GenAI models in secure, compliant environments. Collaborate with MLOps and cloud teams to enable continuous delivery, monitoring, and governance of GenAI systems. Required Qualifications & Experience Education: Bachelor's or Masters degree in Computer Science, Artificial Intelligence, Data Science, or related technical field . PhD is a plus. Experience: 12–15 years in AI/ML and software engineering, with 3+ years focused on Generative AI and LLM-based architectures . Core Skills Deep expertise in machine learning , natural language processing (NLP) , and deep learning architectures . Hands-on experience with LLMs, transformers, fine-tuning techniques (LoRA, PEFT) , and prompt engineering . Proficient in Python , with libraries/frameworks such as Hugging Face Transformers, LangChain, OpenAI API, PyTorch, TensorFlow . Experience with vector databases (e.g., Pinecone, FAISS, Weaviate) and RAG pipelines . Strong understanding of cloud-native AI architectures (AWS/GCP/Azure), containerization (Docker/Kubernetes), and API integration. Architectural & Leadership Skills Proven ability to design and deliver scalable, secure, and efficient GenAI systems . Strong communication skills for cross-functional collaboration and stakeholder engagement. Ability to mentor engineering teams and drive innovation across the AI/ML ecosystem. Nice-to-Have Experience with multimodal models (text + image/audio/video). Knowledge of AI governance, ethical AI, and compliance frameworks . Familiarity with MLOps practices for GenAI , including model versioning, drift detection, and performance monitoring.

Job Title: Executive Human Resource Business Partner (HRBP) Location: Gurgaon Company: IGT Solutions Pvt. Ltd. Industry: IT & BPM – Travel, Transportation, and Hospitality Domain Company Overview: IGT Solutions Pvt. Ltd. is a global leader in IT and Business Process Management (BPM) services, dedicated to delivering innovation and operational excellence across the Travel, Transportation, and Hospitality sectors. With over 10,000+ travel industry experts and 15 state-of-the-art delivery centers worldwide, IGT offers comprehensive solutions in Application Development, Mobility, Testing, Analytics, Contact Center Services, Back Office Operations, and Consulting. IGT is committed to a diverse and inclusive workplace and provides equal employment opportunities without regard to age, gender, race, religion, disability, or other protected statuses. Job Summary: We are seeking a dynamic and experienced Executive – HR Business Partner (HRBP) to join our team in Gurgaon . This role will lead HR operations for the assigned vertical/process, support business functions, drive employee engagement and retention initiatives, and ensure policy compliance. Key Responsibilities: Employee Relations: Address and resolve employee queries and concerns efficiently; track and report resolution Turnaround Time (TAT). Compliance & Policy Adherence: Enforce labor laws, company discipline, and the Code of Conduct. Attrition Management: Maintain attrition at or below 5%. Employee Engagement: Lead engagement activities, facilitate action planning, record meeting outcomes, and ensure timely follow-ups. Performance Management: Ensure timely KRA sign-offs for new joiners and during internal movements; monitor half-yearly and annual appraisals. Training Compliance: Track training plan adherence for the assigned vertical/process. Exit Management: Conduct exit interviews, analyze survey data, and present actionable insights and trends. Retention Strategies: Implement effective strategies to enhance employee retention and workplace satisfaction. Branding & Market Intelligence: Support employer branding and monitor industry HR best practices. Policy Compliance: Ensure adherence to internal policies including Security, Privacy, Zero Tolerance, Disciplinary, and Learning Agreements. Qualifications: Education: Graduate in any field (preferably with a degree in Psychology, Industrial Relations, or Human Resource Management). Experience: Proven experience in HR Generalist or Specialist roles, especially in labor relations and employee engagement in a BPO/Call Center environment. Skills & Competencies: Proficiency in MS Office tools (Excel, PowerPoint, Word) Strong analytical and problem-solving skills Basic understanding of labor laws and HR practices Ability to multitask and manage deadlines Excellent verbal and written communication skills Strong interpersonal and conflict-resolution abilities Additional Information: Work Environment: Onsite role (Gurgaon office) Work Schedule: Flexibility to work in rotational shifts or 24/7 schedules is mandatory Why Join IGT Solutions? Become part of a global leader that drives meaningful transformation in the travel and hospitality domain. At IGT, you’ll have the opportunity to shape HR practices, contribute to a culture of excellence, and grow your career in a dynamic, people-first environment.

You'll be Responsible for: Design, develop and implement cutting-edge AI/ML solutions, including Large Language Models (LLMs) and Generative AI applications Lead projects end-to-end while mentoring team members in AI-ML, including traditional ML and emerging AI technologies Drive innovation in AI agent development and orchestration for automated decision-making systems Establish best practices for responsible AI development and deployment What you'd have: AI-ML Engineer or Data Scientist with 3 11 years of relevant experience Strong expertise in modern AI frameworks and tools: ML/DL frameworks (TensorFlow, PyTorch, Keras, Sklearn) LLM frameworks (LangChain, LlamaIndex, CrewAI, AutoGen) Vector databases (Pinecone, Weaviate, ChromaDB) – Good To Have Hands-on experience with: Generative AI and foundation models Prompt engineering and LLM fine-tuning AI agent development and orchestration RAG (Retrieval-Augmented Generation) systems Proven experience in data preparation, including: Advanced data preprocessing techniques Feature engineering Data quality assessment and improvement Proficiency in data exploration tools (Pandas, Numpy, Polars) Strong programming skills in Python; R is a plus Deep understanding of: Statistics and probability ML/DL algorithms AI governance and responsible AI practices Experience with: Large-scale data processing Model deployment and MLOps Cost optimization for AI systems Track record of 3-5 successful AI/ML projects in production Excellent communication skills and team leadership ability Continuous learning mindset for emerging AI technologies Skills: Statistics and Mathematics Classical Machine Learning Deep Learning and Neural Networks Generative AI and LLMs Agentic AI Development MLOps and Production Engineering Data Engineering Model Optimization and Tuning AI Governance and Ethics Team Leadership Why join us? Impactful Work: Drive innovation in AI technologies while safeguarding Tanla's assets, data, and reputation Growth Opportunities: Be part of a rapidly growing company in the telecom and CPaaS space, with clear paths for professional advancement Innovative Environment: Work with a world-class team on cutting-edge AI technologies in a challenging and collaborative environment Research Opportunities: Contribute to the advancement of GenAI and Agentic AI technologies Tanla is an equal opportunity employer. We champion diversity and are committed to creating an inclusive environment for all employees. www.tanla.com

Role & responsibilities esponsibilities 1Design develop test and implement AI and ML models using the latest technologies and frameworks 2Analyze and interpret complex data to identify trends patterns and insights 3Work with AI lead to understand business objectives and requirements and develop solutions to solve complex problems 4Maintain uptodate knowledge of latest AIML trends techniques and technologies 5Collaborate with data engineers to build data and model pipelines 6Conduct research and implement new methodologies in AI and ML ESSENTIAL SKILLS COMPETENCIES Minimum 5to 6 years of experience in implementing AI and ML models Excellent problemsolving skills with the ability to work independently as well as collaboratively in a team Solid understanding of machine learning algorithms and principles and their applicability to different problems Proficiency in Python and familiarity with libraries like TensorFlow Keras PyTorch or similar ML libraries Experience with GenAI would be highly beneficial Strong communication and presentation skills Skills Mandatory Skills : Prompt Engineering & RAG Good to Have Skills : Fine Tuning Large Language Models Preferred candidate profile

machine learning algorithms and deep learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) Proficiency in Python data processing libraries (Pandas, NumPy) Knowledge of cloud platforms like AWS, GCP, or Azure NLP,LLM,GenAI