Why FDE
Forward Deployed Engineer is the role of the moment because production AI is the work of the moment.
What FDEs do, why every serious AI company hires them, and where the comp premium comes from.
02 / The role replacing it
Forward Deployed Engineer is the job that absorbs everything fullstack used to be — and adds the work fullstack didn't cover.
Palantir invented the title. OpenAI productionized it. Anthropic, Scale, Salesforce, and every serious AI infrastructure company now hires for it under one name or another: Forward Deployed Engineer, Solutions Engineer, AI Engineer, Applied AI. The work is the same. Take a model that mostly works. Make it actually work, inside a real client's mess.
Greenfield is easy. Production AI inside a Fortune-500 codebase, with a CTO who wants weekly demos and a CISO who wants their concerns answered, is hard. Few engineers can do it. The engineers who can are the ones being hired.
What an FDE actually does
- Deploy AI systems inside a client's codebase, infra, and data — not in a sandbox.
- Own the eval loop: define what "working" means, measure it, defend the number.
- Translate fuzzy business asks into scoped engineering work, then push back when the ask doesn't survive contact with reality.
- Sit across the table from a CTO on Tuesday and write production Rust on Wednesday.
What the bar looks like
Hiring loops at the AI labs and applied-AI firms screen for evals you have shipped, RAG systems you have measured (not just built), and client-style discovery you can demonstrate on demand. The engineers who clear it have been doing this work for at least one year. This program is how you build that year.