Forward Deployed Engineer

AI Consulting. US Remote with ~25% client travel. Full-time.

About the Firm

We are a boutique AI consulting firm. We partner with Fortune 500 leaders in telecommunications, healthcare, financial services, and technology to design, build, and operationalize AI solutions that move the business. Our model is intentionally lean. Small, senior teams own outcomes end to end.

The Forward Deployed Engineer (FDE) sits between our Sales organization and our delivery work. You will be one of a small group of senior FDEs who shape how multi-million dollar AI transformation programs get scoped, sold, and delivered. Roughly half of your time is spent in front of clients. You will co-design solutions with C-suite sponsors and partner with Account Executives and Customer Sales Engineers in pursuit cycles.

The other half is spent with your hands on the keyboard, building reference architectures, prototypes, and the production systems behind them.

This is not a slide-deck consulting role. FDEs at this firm write code, debug production agents, defend architecture decisions in front of CIOs and Chief Risk Officers, and own the technical narrative from the first discovery call through post-deployment expansion. We are looking for engineers who have already done this work, who can hold a room of skeptical executives and ship a working system the same week.

Required

• 4 to 12 years of engineering experience, with the last several years spent shipping production AI and ML systems in real customer environments. Prototypes and research projects do not count on their own.
• Deep domain experience delivering complex software or AI solutions inside Fortune 500 or regulated enterprises in at least one of:
  Telecommunications, Healthcare and Life Sciences, Financial Services, or Technology.
• Hands‑on experience with modern LLM systems. This includes prompt engineering, RAG, fine‑tuning and adapters, agentic frameworks (Lang Graph, CrewAI, MCP, or equivalents), tool use, evals, and guardrails. You should have strong opinions about when to use which.
• Production‑grade Python proficiency. Working knowledge of at least one major cloud (AWS, Azure, or GCP), containerization (Docker and Kubernetes), and modern data platforms (Snowflake, Databricks, Big Query, or similar).
• Solid foundation in classical ML and data engineering. This includes feature pipelines, model evaluation, experiment tracking, vector stores, and streaming and batch ETL.
• Pre‑sales and solutioning experience. You have personally led discovery, scoping, and SOW shaping with enterprise buyers, and you have stood next to an Account Executive in a multi‑million dollar pursuit.
• Strong executive communication skills. You can present to a Board, whiteboard an architecture with a CTO, and explain a model failure mode to a Chief Risk Officer in the same afternoon.
• Consulting‑grade delivery instincts. Comfort with ambiguity, bias for shipping, and judgment about when a system is ready for production versus when to keep iterating.
• Willingness to travel up to ~25% to client sites in the U.S., typically Monday through Thursday during active engagements. Must be authorized to work in the U.S.