Forward deployed engineer: the career recruiters called job-hopping

Why everyone is talking about FDEs now

The role comes from Palantir, which has had engineers building on-site at clients for years. OpenAI and Anthropic have hundreds of openings for it. Aaron Levie, CEO of Box, announced on X on April 30 that Box will hire and retrain internal forward deployed engineers to get agents working on critical business processes.

Uber built a structure around it: agentic pods, where its most AI-capable engineers sprint for two weeks with a domain expert from finance, legal or marketing. Sixteen pods in two months. One pod cut budget decisions across 150 cities from 15 hours to 30 minutes (X thread by Uber’s CTO, July 2026).

The Netherlands too. Deloitte, Accenture, Capgemini and McKinsey told Dutch financial daily FD that their clients increasingly ask for this profile: engineers who design, build and embed AI applications in day-to-day operations. According to Capgemini, companies are past the experimentation phase and want to know how to run AI at scale. The big firms are recruiting for it and retraining existing staff (FD, 24 August 2026).

Last spring a Dutch IT director posted a LinkedIn vacancy for an “AI-native colleague”: no traditional role, no fixed department, someone who talks as easily as they build. That is the FDE profile without the name. Directors ask me the same question: where do I find this person?

I did this job before it had a name

My CV: the app team at KPN, marketing intelligence at insurer Reaal, the acquisition team at Eneco, Head of Data at ride-hailing platform Free Now in Hamburg. Then I co-founded an AI consultancy, which I handed over this summer. I never stayed anywhere longer than two years; recruiters saw a risk.

The work was the same everywhere, only the domain changed: telecom, insurance, energy, mobility, AI. Land in a business team, learn the systems, build what is needed, bring people along, make myself redundant and move on. Free Now was the same kind of platform as Uber, now the textbook example of this way of working.

A career path that fit no org chart in 2015 is the profile companies ask for in 2026.

Examples of my work

Four types of work, each built with the people who will use it. What exactly I build for which client stays confidential.

Learning platforms

Building or rebuilding a digital learning environment, including moving existing course material to the new platform. I build the platform and the migration; whoever manages the courses tests along until they can carry on alone.

Business software

Internal software for people’s everyday tasks. I start from the work itself: what do people now do by hand or in loose files, and what should the application take over? Then I build in short rounds and test with the people who will use it.

Product development

Building on software that already has users: new features, bug fixes and maintenance. I work inside the existing team and codebase, and decide with the team what users need first.

Process automation

Software that takes over recurring tasks or shortens them. A fixed part of the job is drawing the line: what may the software handle alone, and in which cases does a person check before anything goes out?

What comes after the application: an agent and an owner

The next step of this trade is already visible. Dan Shipper of Every, which runs its own consulting practice through an agent in Slack, puts it this way: “every agent needs a human” and “the further away an agent is from a human who’s doing it, the worse it does” (TBPN, 22 May 2026). Gartner expects over 40% of agentic AI projects to be cancelled by the end of 2027, over cost, unclear value or inadequate oversight (25 June 2025).

For an FDE that means the handover includes someone who owns the agent. Since August 2026 my handover has therefore been a fixed list of five points. That is what I settle on, and I leave only once all five are in place.

One owner

One name inside your organisation that owns the system. Not IT, not me.

An evaluation set that keeps running

The test set I build against runs on your machine. If the score drops, you see it first.

A one-page runbook

What it does, what it must not do, where to look when it stalls.

Who steps in

An agreement on who corrects a mistake, and a button to do it.

A path for the next model version

The model that works today can be replaced within six months. Who retests then, and when?

A caveat on that list

The list is younger than most of the projects I draw on, so the project descriptions above do not claim that every handover is complete. Ask any agency, me included: what do you leave behind, and who owns it then?

What does a forward deployed engineer earn?

In the US the median base salary is $210,000. The 25th percentile earns $165,000, senior and staff profiles reach $243,000 (Recruiting from Scratch, based on 300+ technical placements, 2026).

In Europe, London is the only city with usable data. There the median total compensation, including stock and bonus, is £141,000 a year. The 25th percentile of that total sits at £102,000, the 75th at £178,000 (Levels.fyi, updated 25 September 2026). For the Netherlands, Levels.fyi has no FDE entries yet.

That scarcity is the real problem. Recruitment firm Christian & Timbers mapped over 17,000 FDEs in the US; only about 2,000 of them have implemented AI at large organisations more than once with demonstrable results (cited in FD, 24 August 2026). You compete for this profile with OpenAI, Anthropic, Palantir and, since this year, the big consulting firms. For most Dutch companies the price is the smallest question. The bigger one: can you land this person, and do you have enough work to keep them?

When you should hire one in-house

Sometimes this role belongs on the payroll. That depends more on where you are stuck than on company size. Do you have an established IT landscape, your own data team and a sizeable marketing and sales operation, with the delay sitting mostly in communication between departments and the question of who is responsible? Then hire someone who stays, learns the dynamics and can be held to account.

The IT director with that vacancy is getting it right. An outside builder who leaves after four weeks does not settle who is responsible between departments.

When bringing in the work is the better call

With 50 to 500 employees and no data team, this hire is the wrong solution. You will not win the talent fight with the labs. And if you do, that person runs out of things to build after the first bottlenecks are solved.

The big consulting firms feel the same pressure. Nicole van Det, CEO of Accenture Netherlands, told FD that AI and tech companies increasingly deploy engineers directly at clients to get from prototype to real use, and calls that a new competitive field (FD, 24 August 2026).

What you need then is the work, not a permanent job: someone who builds in your systems, shows that it runs and then leaves. That is what I do, for a fixed price with an end date. You get my verdict up front, even when it is that you should hire someone instead.