They see the real workflow
Sit inside the work and you find the problems no discovery call surfaces — the spreadsheet everyone hates, the handoff that drops orders.
HumanAI · Forward Deployed Engineers
The AI engineers you can't hire.On your team next week.
Forward deployed engineers (FDEs) build inside your business — the role Palantir coined and every AI lab now fights to staff. Ours come fractionally: only the hours you actually need.
Senior engineers, vetted · Fractional hours · We manage them, you get the results
The role
What is a forward deployed engineer?
A forward deployed engineer is a software engineer who works inside a customer's business instead of at their employer's office. Palantir coined the term; OpenAI, Anthropic, and most serious AI companies now hire for it. The job: learn how the business actually runs, then build working software where the work happens.
That last part is what separates an FDE from every advisor you've met. They don't write recommendations for someone else to implement. They ship — automations, integrations, internal tools — and they keep shipping as the business changes.
The model works so well that FDE roles are now among the most fought-over jobs in AI. Which creates a problem for everyone else: the engineers best at embedding in a business like yours keep getting hired by companies that aren't yours.
Why it works
Embedded beats advisory. Every time.
The FDE model spread because it delivers. We built our whole company on the same conviction.
Software built next to its users gets used
When the builder sits with the people using the tool, feedback lands the same day. Adoption stops being a rollout project.
Iteration doesn't stop at launch
The first version is a starting point. An embedded engineer keeps tuning it in production, where the results actually happen.
Our take
They say forward deployed engineer. We say AI Architect.
"Forward deployed" describes where the vendor puts its engineer — the subject of that sentence is the seller, and the engineer is there, first and foremost, to make one platform succeed. We named the role for you instead: an AI Architect designs what your business needs, then builds it. And not the kind of architect who hands off the drawings — ours stay through the build.
In practice
Same intent. Different execution.
The embedded model, minus the platform agenda. Here's what changes when the engineer works for your business.
Deployed for you, not a platform
A vendor's FDE is there to make that vendor's product succeed. Our Architects are tool-agnostic: they recommend, adopt, or build whatever actually fits your business.
They envision and build
No plans-then-handoff. The person who maps your workflows is the person who builds the automations and tools — and iterates on them in production with your team.
Fractional, not full-time
Lab FDEs come full-time, usually attached to a platform contract. Ours come at 25%, 50%, or 100% of a week. You buy the hours your business needs and not one more.
Accountable for outcomes
Success isn't measured in product adoption. It's measured in working software your team still uses in month six.
The offer
Fractional. Which is the whole point.
The experienced AI engineers you can't hire full-time — for exactly the hours your business needs.
25% of their week
The starting point for most. One or two priority workflows, shipped and maintained — and it outbuilds a full-time junior hire.
50% of their week
A pipeline of builds: several departments, integrations between systems, and a roadmap that keeps moving.
100% of their week
A full-time embedded engineer — without the recruiting war, and without the payroll line.
Book a call
We scope the right fraction on the call.
Week one
First call, workflow mapping, and the first build scoped.
Month one
First automations live in production, with your team using them.
Quarter one
A stack of working tools nobody wants to give back.
Questions
Asked before every engagement.
What is a forward deployed engineer?
A forward deployed engineer (FDE) is a software engineer who works inside a customer's business rather than at their employer's office. Palantir coined the term, and OpenAI, Anthropic, and other AI companies now hire for the role. FDEs learn how a business actually operates, then build and ship working software on site — automations, integrations, and internal tools — instead of handing over recommendations.
What does a forward deployed engineer actually do?
They embed with your team, map how work really flows, and build AI tools that fit — then keep improving them in production. Typical output includes workflow automations, system integrations, internal tools, and AI agents, plus training so your team actually uses what gets built.
How much does it cost to hire a forward deployed engineer?
At the AI labs, forward deployed engineers earn well into six figures, and most never reach the open job market. HumanAI provides the same profile fractionally: you pay for 25%, 50%, or 100% of an engineer's week — a fraction of the cost of a full-time hire. Book a call and we'll scope exact pricing with you.
Can you hire a forward deployed engineer part-time or fractionally?
Yes — that's exactly what HumanAI does. Most growing companies don't need a full-time FDE, and can't win the bidding war for one anyway. We place vetted senior engineers at 25%, 50%, or 100% of their week, and we recruit, train, and manage them for you.
What's the difference between a forward deployed engineer and an AI consultant?
A consultant studies your business and leaves you recommendations. A forward deployed engineer builds. The deliverable isn't a report — it's working software, shipped inside your team and improved in production.
Is a forward deployed engineer the same as an AI architect?
At HumanAI, our AI Architects fill the same role a forward deployed engineer fills — embedded, hands-on, shipping working software. The difference is outlook: an FDE is usually deployed by a vendor to make that vendor's platform succeed, while our Architects are tool-agnostic and work for your business. They design the solution, then build it. We break the differences down in our article "AI Architects vs Forward Deployed Engineers."
How fast can a forward deployed engineer start?
Usually within a week. The engineers are already recruited and vetted — there's no months-long search. Most engagements begin with a first call, a workflow-mapping week, and a first build scoped by week two.
Do only big AI companies use forward deployed engineers?
No. The labs made the role famous, but the model fits any business with real workflows and no time to babysit an AI initiative. Growing companies are where one embedded engineer moves the needle most — fewer layers in the way, and more obvious wins.
The role every AI lab fights over. On your team, fractionally.
A forward deployed engineer's skill set, an AI Architect's outlook — embedded in your business, usually within a week.