Job highlights

- Hands-on experience with AWS Bedrock, Python FastAPI, Kafka, Java Spring Boot, Snowflake, SQL; robust knowledge of LLMs, RAG architecture, and multi-agent frameworks

- Design and implement agentic AI solutions using AWS Bedrock; build serverless architectures with AWS Lambda, Step Functions, and EventBridge; develop prompt engineering strategies; integrate LangChain or Bedrock AgentCore; implement RAG workflows and knowledge bases; collaborate with cross-functional teams

Must-Have Skills:

- Hands-on experience with AWS Bedrock, Python FastAPI, Kafka, Java Spring Boot, Snowflake, SQL.

- Strong knowledge of LLMs, RAG architecture, and multi-agent frameworks.

Good-to-Have Skills:

- Knowledge on Core Python.

- Knowledge on Cloud platforms, GraphQL.





Responsibilities / Expectations from the Role:

- Design and implement agentic AI solutions using AWS Bedrock, including Agents, Knowledge Bases, and Guardrails.

- Build serverless architectures with AWS Lambda, Step Functions, and EventBridge for AI agent workflows.

- Develop prompt engineering strategies (chain-of-thought, tree-of-thought, React) for multi-step reasoning.

- Integrate LangChain or Bedrock AgentCore frameworks for orchestration.

- Implement RAG (Retrieval-Augmented Generation) workflows and knowledge bases.

- Collaborate with cross-functional teams to deliver scalable AI solutions.

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