Classic AI consulting hands you a report, a few slides and a roadmap. The problem: between the recommendation and a system running in production lies a gap nobody crosses. The Forward Deployed Engineer (FDE) model fills exactly that gap.
What is a Forward Deployed Engineer?
It's not a consultant. It's an engineer who settles into your teams: joins your standups, works in your repo and tools, writes the code and ships it. The concept was invented by Palantir in the early 2010s (a role called “Delta”) to turn a signed contract into working software.
Why the model is exploding in 2025-2026
- ▸FDE job postings surged 800% in 2025 (OpenAI, Ramp and a wave of AI startups are adopting it).
- ▸In the age of agents, the distance between a POC and production has become fatal: you need someone in the loop, not beside it.
- ▸Models evolve too fast for a frozen deliverable: you have to iterate in the client's real context.
- ▸The real value is in the domain context, and you only capture it from the inside.
What it changes for your company
You no longer buy a diagnosis, but execution. The engineer accelerates what exists instead of bolting on an external solution, your teams upskill alongside them, and you don't stay dependent on a black box. The result: real things in production, not intentions.
That's exactly our in-house deployment lever: we embed a squad of premium AI engineers who cover the entire value chain, from engineering to marketing.