Experience: 5 - 10 years

Location: Hyderabad/Mumbai/Bangalore/Indore/Chennai/Gift :

- Strong hands-on experience building AI/LLM-powered systems end-to-end.
- Expertise with LangChain and LangGraph.
- Deep proficiency in Python for Al pipelines, APIs, and orchestration.
- Strong understanding of embeddings, chunking, retrieval architectures, and ranking strategies.
- Experience with open-source LLMs (Llama, Mistral, Falcon, Mixtral, etc.)
- Experience deploying full-stack enterprise applications.
- Experience with vector database design and optimization.
- Robust knowledge of Kubernetes, Docker, CI/CD, microservices, and cloud deployment patterns.
- Bands-on experience integrating solutions with Microsoft Copilot.
- Experience with Al evaluation, observability, and model governance Key responsibilities:
- Design and implement full end to end RAG pipelines (ingestion, chunking, embeddings, retrieval, ranking)
- Build scalable Al workflows using LangChain, LangGraph, and agent-based architectures.
- Develop backend services and APIs in Python, ensuring scalability,



security, and maintainability.
- Create full-stack UIs for GenAl applications (React, Angular, Vue, etc.)
- Integrate and optimize vector databases (Pinecone, ChromaDB, Weaviate, Milvus)
- Implement Microsoft Copilot integrations across enterprise workflows and apps.
- Build evaluation frameworks, observability pipelines, and quality guardrails using tools such as RAGAS, LangSmith, or custom evaluation metrics.
- Implement enterprise authentication and access (OAuth, Azure AD, Okta)
- Optimize model performance, inference latency, indexing strategies, and retrieval accuracy.
- Ensure proper DevOps (Docker, Kubernetes), CI/CD, and release management for all Al components.
- Collaborate with cross-functional teams to drive Al adoption and ensure scalable, maintainable solutions.
- Provide long-term support, model updates, error handling, and operational governance

📌 Generative AI Engineer (Bengaluru)
🏢 Tata Consultancy Services
📍 Bengaluru