Key Responsibilities
- Design, develop, and deploy AI-powered applications using LLMs, Agentic AI frameworks, and modern AI architectures.
- Build and orchestrate multi-agent systems using LangGraph, A2A, MCP, and related frameworks.
- Design and implement scalable RAG pipelines using vector databases, embeddings, and semantic search.
- Develop REST APIs and AI services using Python, FastAPI, and Pydantic.
- Integrate AI solutions with AWS, Azure, or GCP cloud services.
- Build and optimize prompt engineering, tool-calling, and agent workflows.
- Develop LLM evaluation, monitoring, and optimization frameworks.
- Create AI-driven user experiences and business workflows powered by intelligent agents.
- Collaborate with business, compliance, IT, and data teams to deliver enterprise AI solutions.
- Leverage AI-assisted development practices for code generation, testing, documentation, and refactoring.
- Implement cloud-native deployment strategies using Docker, CI/CD, and modern DevOps practices.
- Stay updated on emerging GenAI, Agentic AI, and LLM technologies.

Required Skills




- 8+ years of Software Engineering or Data Science experience.
- Minimum 2+ years of hands-on experience in Generative AI, LLMs, or Agentic AI solutions.
- Robust expertise in Python development.
- Experience building AI Agents using LangGraph and related agent frameworks.
- Strong knowledge of LLMs, embeddings, prompt engineering, and tool integrations.
- Hands-on experience with Retrieval-Augmented Generation (RAG) architectures.
- Experience developing APIs using FastAPI and Pydantic.
- Experience with MCP (Model Context Protocol) and A2A integrations.
- Knowledge of cloud platforms such as AWS, Azure, or GCP.
- Experience with Docker, CI/CD pipelines, and cloud-native architectures.

Preferred Skills
- Insurance or Annuities domain experience.
- Experience with Azure OpenAI, AWS Bedrock, Vertex AI, or similar AI services.
- Vector databases such as Pinecone, Weaviate, Chroma, or OpenSearch.

📌 GenAI / Agentic AI Engineer (LLM, LangGraph, RAG) (Hyderabad)
🏢 Tata Consultancy Services
📍 Hyderabad