Hire Forward Deployed Engineers: senior AI engineers inside your operation

Hire forward deployed engineers who join your team, find high-value AI use cases in the real operating environment, and ship working systems alongside the people who will use them.

Discuss a forward deployment AI implementation

Hire forward deployed engineers: a team working through process maps around a table

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Why the use case has to be found on site

The expensive work in a business is rarely written down. It lives in the spreadsheet somebody rebuilt, the approval that waits two days, the document everyone re-reads. A consultant interviewing that process gets a description of it. An engineer sitting inside it for a month sees what is actually happening, and can build against it the same week.

How forward deployed engineers differ from consulting and staffing

Both of the other models are legitimate and we offer them. Forward deployment is a third thing, and it is the right choice less often than it is sold.

Forward deployment
What it is
A senior AI engineer works inside the operating environment, finds the use case there, and ships it with the team that will use it.
What you get
A working system and a team that knows why it works.
Where it stops
It needs real access to the work and to the people doing it. Without that it is just staffing.
Consulting
What it is
An outside team studies the problem and returns a recommendation.
What you get
Analysis, a decision you can defend, a plan.
Where it stops
The people who understood it most deeply leave when the document is delivered.
Staffing
What it is
An engineer joins your team and builds what the backlog says.
What you get
Capacity and skill, inside your process.
Where it stops
The backlog is the limit. Nobody is paid to find the use case nobody wrote down.

How it works

1
Deploy into the environment
The engineer joins the team that owns the work, with access to the systems and the people, not a summary of them.
2
Find the candidates in the open
Where time, cost and error actually concentrate, observed in the operating environment rather than collected in a workshop.
3
Ship the smallest useful system
Built against the real systems, with human sign-off at every committing step and the deterministic parts kept deterministic.
4
Hand it to the people who use it
Evaluation, monitoring and the knowledge to change it, left with your team rather than carried away.

When to hire forward deployed engineers

Forward deployment costs more attention than a staffed role and more commitment than a consulting engagement. It is worth it in some situations and wasteful in others.

Choose it when

The work is complex, regulated or deeply operational, and it does not survive being described in a workshop.
Leadership believes there is value in AI here but cannot say where, and would rather find out than commission an opinion.
A previous AI effort produced a pilot nobody uses, because it was built away from the work.
The people who do the work can give an engineer real access for the length of the engagement.

Choose something simpler when

The use case is already defined, agreed and scoped. That is a Statement of Work, and it is cheaper.
You need capacity on an existing backlog. That is a full-time specialist from Engineering talent.
Nobody can give the engineer access to the operating environment. Without access this model has no advantage over staffing.

Engagement models for forward deployed AI engineers

Embedded engineering on a monthly rate, the same commercial shape as a full-time specialist. Where a discovery is needed first, it is contracted separately so you are not committing to a build before anyone knows what it is.

Embedded engineering
Best for
Finding and shipping use cases inside the operating environment
How it works
Monthly rate per engineer, with the deployment length agreed up front
Discovery first
Best for
An organisation that wants the opportunity priced before it commits
How it works
Paid opportunity assessment, contracted separately, then a deployment or a Statement of Work