- 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
Technology->Machine Learning->Generative AI->retrieval augmented generation (rag),Technology->Artificial Intelligence->Artificial Intelligence - ALL,Technology->data science->PYTHON
