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.
• Build functional applications using large language models (LLMs) and APIs (e.g., OpenAI, Anthropic, open-source Llama).

Requirements

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 Qualifications

• 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).