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
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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.