Role Purpose :

Hands on engineer to build Python based GenAI and AWS Bedrock solutions, contributing to RAG pipelines, agent workflows, and production-ready AI features under senior guidance.

Key Responsibilities :

- Develop GenAI features and workflows using Python and AWS Bedrock.

- Implement RAG pipelines (chunking, embeddings, retrieval, grounding).

- Build single/multi-step agent workflows using LangChain / LangGraph.

- Integrate LLMs with APIs, tools, and enterprise applications.

- Write tested, maintainable Python code with CI/CD pipelines.

- Monitor basic latency, token usage, and cost metrics.

- Collaborate with architects, seniors, and QA teams.

Must Have Skills :

- Python - Core concepts: OOP, typing, modules, pytest/unittest, fixtures, basic async.

- AWS Bedrock - Model invocation (Claude/Titan, etc.), Knowledge bases or retrieval integration, basic understanding of guardrails & access controls.

- Generative AI - Prompting (system, few-shot), RAG types and approaches, Basic evaluation awareness, LangChain / LangGraph, Simple agent flows and routing.

- DevOps Basics - Git, PRs, CI pipelines, Docker basics, artifacts.

Good to Have :

- Vector DB exposure (OpenSearch, FAISS, Pinecone, etc.).

- Kubernetes awareness, ML basics (metrics, cross val, leakage awareness).

- Understand requirements clearly.

- Good communication and learning mindset & Team-oriented execution.