Lead Engineer - App Engg & AI
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Role details
Tech stack
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Job description
ResponsibilitiesTranslate 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 harnessRun agile ceremonies for the pod; produce estimates and sprint plansApp Development: Build functional applications using large language models (LLMs) and APIs (e.g., OpenAI, Anthropic, open-source Llama).Required Qualifications7+ 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.PreferredConsulting 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).
Requirements
- 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).
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