Senior Lead GenAI Engineer
Summary
A senior hands-on lead who architects and builds a stateful headless GenAI application for grounded, personalized content creation — designing multi-agent orchestration, APIs, RAG, streaming interfaces, and observability while reviewing other engineers' work. Core stack is Python or TypeScript on AWS with Amazon Bedrock and AgentCore.
You will architect and build a stateful headless GenAI application for grounded, personalized content creation. You will design multi-agent orchestration, APIs, structured outputs, integrations, streaming interfaces, evaluation and observability capabilities, and critical production code while reviewing other engineers’ work.
Responsibilities
- Design and build a stateful headless GenAI application
- Propose architecture and make key technical decisions
- Build multi-agent orchestration and multi-turn application flows
- Design API-first architectures and structured contracts
- Integrate GenAI applications with enterprise platforms, data services, and content repositories
- Build RAG, grounding, memory, evaluation, and observability capabilities
- Build streaming interfaces with clarification flows, conversation history, and error handling
- Render structured responses including tables, charts, citations, and reusable results
- Establish coding patterns, review engineers’ work, and produce production code
Requirements
- Significant hands-on experience architecting and building production GenAI applications
- Python or TypeScript software engineering and microservices experience
- Experience with stateful multi-turn and multi-agent orchestration
- API-first architecture and structured-contract design experience
- Experience building headless services with structured outputs
- Experience integrating GenAI applications with enterprise platforms, data services, and content repositories
- Experience with RAG, grounding, application state, memory, evaluations, and production observability
- Experience building streaming multi-turn GenAI interfaces
- Ability to establish coding patterns, make technical decisions, review engineers’ work, and produce production code
- AWS, Amazon Bedrock, and AgentCore experience