The term "forward deployed engineer" comes from Palantir. It described an engineer who flew out to a customer site, sat in the secure room, learned the workflow, and built software that solved the customer's actual problem.
Not a sales engineer. Not a vendor on a Zoom link. An engineer who shipped code to production inside someone else's organisation.
The model worked because the work that mattered was at the integration layer. Building the right thing for the right user, with their constraints and their data. The hard part was making it actually work for the people who were supposed to use it.
That's where AI is now.
The model is not the bottleneck. GPT-4-class and Claude-class models have been good enough for a year.
The bottleneck is everything else: the eval suite, the data pipeline, the latency budget, the cost per call, the failure modes, the handoff to your on-call rotation. That's what a forward-deployed AI engineer is for.
What it actually looks like
I show up to your Slack, your repo, and your stand-ups for 4 to 12 weeks. I'm in the daily flow with your team, not running a separate workstream behind a status report.
The output is code that ships. Not a recommendations deck. The system runs in your stack, with your data, on your budget, before the engagement ends.
The deliverables are concrete:
- Production code in your repo.
- Docs in your wiki.
- Eval suite committed alongside the code.
- Observability dashboards in your stack.
- A handoff doc the next engineer can read in an afternoon.
If at the end of the engagement your team can't extend the system without me, the engagement failed. That's the test.
Why this model fits AI
AI projects fail in three predictable places.
One. The model works in isolation but breaks on real data. Eval coverage was thin, edge cases weren't tested. Now there's an incident every Friday.
Two. The unit economics don't survive scale. Cost per call was guessed; p95 latency was never a target. Finance is asking why the bill tripled.
Three. The team can't operate it. Built by someone external who left, no runbook, no metrics. The system is a box no one can debug.
A forward-deployed engagement attacks all three. The eval suite goes in first, before anything ships. Cost and latency budgets are agreed in writing, not promised verbally.
The team is in the build, not just the demo. The operational knowledge transfers as the code does.
What it's not
Not staff augmentation. Staff aug is "give me a body for 3 months." Forward-deployed work has a defined outcome and a date.
Not a recommendations exercise. Recommendations are "here's what you should build." Forward-deployed work builds it.
Not a one-shot drop and disappear. The 30-day support window after handoff is part of the contract, not a favour.
Not a contracting marketplace. The engineer on the call is the engineer on the keyboard. No junior backed by a Slack-only architect somewhere overseas.
Who it's for
Teams that meet at least two of these:
- You have a roadmap item that needs senior AI engineering, and a 3-month hire timeline isn't realistic.
- You've started a project internally and it stalled at the integration or eval layer.
- You bought an outside engagement before that delivered slides instead of a system.
- You're a small team and want to add AI capability without permanently growing headcount.
If you're a 5,000-person enterprise with a 6-month procurement cycle, this isn't for you. If you're a pre-seed founder looking for a free prototype, also not for you.
What we don't do
We don't run discoveries that take three months and produce a deck. We don't start without a written plan that includes cost, latency, and eval targets. We don't run black-box engagements where you find out what got built at the end.
The plan goes first. It's free if we don't proceed. It's credited toward the engagement if we do.
That's the offer.
How to know if you need one
Three questions to ask yourself.
- Is there a real AI/ML system on your roadmap that hasn't shipped yet?
- Could you get senior in-house engineering on it in the next 8 weeks?
- If the answer to #2 is no, what's blocking the project until then?
If #1 is yes, #2 is no, and the answer to #3 is "we just need someone to ship it," that's the engagement.