Scaling AI at the Edge: 20 Forward Deployed Engineers in 6 Months

The Brief

A public sector client needed to embed AI capability directly into live operations, not a research team, not a back-office build. They needed engineers who could sit inside real workflows, move fast, and be trusted with mission-critical systems. The target was 20 Forward Deployed Engineers in six months, with no room to lower the bar to hit the number.

The Challenge

Forward Deployed Engineering is one of the hardest roles to hire for in tech. It sits somewhere between elite software engineer, consultant and operator. The talent pool is small to begin with, largely absorbed by Palantir, and public sector clearance requirements shrink it further still. Most firms simply aren't set up to source for something this hybrid, at this volume, on this timeline.

The Approach

We mapped the real talent pool rather than the obvious one: Palantir alumni, defence-tech and gov-tech startup engineers, and elite generalists with genuine client-facing experience. The screening bar was built around what the job actually demands, tolerance for ambiguity, speed of deployment, communication under pressure, rather than generic technical tests.

We ran parallel pipelines instead of sequential ones, keeping four to five times the candidate flow against every open seat, and compressed feedback loops with the client to under 48 hours per stage so strong candidates never went cold.

The Result

20 hires in six months, with no compromise on quality. The client now has a forward-deployed bench capable of shipping AI directly into live operational environments.