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
Technical and Professional Requirements:
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 ________________________________________
