Lead Engineer - App Engg & AI

Responsibilities Translate business outcomes into agent specifications, tool definitions, evaluation criteria, and acceptance gates. Implement production agentic workflows: retrieval, tool orchestration, structured output, human approval loops, failure handling and fallback. Own evaluation for your engagement: define what "good" means, build the harness Run agile ceremonies for the pod; produce estimates and sprint plans App Development: Build functional applications using large language models (LLMs) and APIs (e.g., OpenAI, Anthropic, open-source Llama). Required Qualifications 7+ years in software engineering with 2+ years shipping LLM or agentic systems to production. Hands-on depth in Python or Java/Spring Boot, plus comfort in a modern front-end stack (React/Next.js) when the engagement needs it. Working knowledge of a major cloud (AWS or Azure) including managed AI services, containers, serverless, and IAM. Experience with RAG, vector search, and evaluation methodology — including a clear-eyed view of where retrieval is the wrong answer. Demonstrated technical leadership of a small team on a delivery-pressured project. Strong written and verbal communication; you can write a design doc a client will actually read. Preferred Consulting delivery experience in a regulated vertical (financial services, healthcare, retail data, nonprofit/crisis services). MCP, A2A, or comparable agent interoperability protocol work. Snowflake, Collibra, SODA, or data quality tooling exposure. Experience with contact center or omnichannel platforms (Amazon Connect, Teams, voice).