Forward-deployed engineer
An AI engineer inside your team
Hiring a senior AI engineer takes 6 months — if you find one. A forward-deployed engineer embeds in your organisation within a week and is accountable for the outcome end-to-end, not for hours logged.
First profiles within 1 hour.
to first candidate profiles
from call to start
free at the start if not a fit
to a scaled AI capability
What is an FDE?
The model Palantir invented and AI labs made standard
A forward-deployed engineer works inside the client's organisation instead of building from the outside: your standups, your repo, your domain — with direct accountability for it working in production. You get embedded senior AI capability without the 6-month recruitment pipeline for a profile that barely exists on the market.
[ Days 1–30 ]
Embed & first win
Joins your team, maps systems, data and workflows. Ships a first automation or AI feature — small, real, in production.
[ Days 31–60 ]
Production AI
The first significant AI capability goes live: with evaluation, observability and a rollback path. Your team sees how it is built.
[ Days 61–90 ]
Scale & enable
Expands what works, kills what does not. Trains your engineers on the AI workflow so the capability stays when the engagement ends.
Capabilities
What your FDE brings
Engagement models
Three ways to engage
[ Retainer ]
Full-time embed
The default. One engineer, fully inside your team, your standups, your repo. Monthly retainer.
[ Advisory ]
Part-time advisory
2–3 days a week. Right when an internal team executes and needs senior AI direction, review and unblocking.
[ Fixed price ]
Project-based
Defined scope, defined timeline, fixed price. When the outcome is clear and bounded.
FDE vs hiring
Why not just recruit?
In-house hire
- 3–6 months of recruiting
- Whoever accepts the offer
- A bad hire costs months
- Permanent headcount
Forward-deployed engineer
- Start in about a week
- Senior only, vetted on delivery
- First 2 weeks free if not a fit
- Monthly — scale up or down
FAQ
Before you ask
How is this different from a regular contractor or consultant?
A consultant advises and leaves; a contractor executes tickets. A forward-deployed engineer sits inside your organisation, owns an outcome end-to-end, and is accountable for it working in production — the model scaled by Palantir, OpenAI and Anthropic.
How do you measure outcomes?
We agree on the metric before starting — hours saved, lead time, throughput, error rate. The FDE reports against it, not against hours logged.
Who owns the IP?
You do. Code, prompts, evaluation sets, infrastructure — everything built during the engagement belongs to you.
What access does the engineer need?
Repository access, the workflow tools your team uses, and the people who know the processes. Data access is scoped case by case, GDPR-first, with a DPA in place.
Can the FDE train our own team?
That is half the point. Enablement is built into the engagement — the goal is that your team keeps shipping with AI after we leave, not that you depend on us forever.
Get matched
Matched with an FDE in days, not months
We reply within 1 business day.
The profile you can't hire is one call away
Tell us the outcome you need. You'll see matching profiles within an hour.