SaaSPositioningPipeline
Embedded engineers · led by us
Forward-deployed engineers
An AI engineer inside your team, or your customer's, until the AI is in daily use. We scope the role, find and vet the engineer, and lead the work.
Who it is for: AI, SaaS and IT services companies whose customers stall at go-live, and businesses rolling out AI that need an engineer on the inside.
- How long
- Agreed per requirement
- You deal with
- One firm, us
The problem
Software that works in a demo often stalls inside a customer: real data, security reviews, old systems and people who were never asked. Forward-deployed engineers exist for that gap. The role started at Palantir and is now used by OpenAI, Anthropic and Salesforce, and job postings for it rose more than 800% in 2025 (Salesforce).
Good ones are hard to find, and harder to manage from a distance.
What you get
- The use case and the role scoped before anyone is matched
- An engineer vetted on shipped work, not on a CV
- A project lead who keeps the work on track and reports to you
- One agreement and one point of contact
- When the work ends: documentation, tests and a team that can run it
How it works
Understand
The use case, the skills it needs and what success looks like.
Match
We find and vet the right engineer through our global network of specialist partners.
Lead
A project lead keeps the work on track and reports to you.
Hand over
Documentation, tests and training, so your team can carry on without the engineer.
What we vet for: production code shipped into customers' systems, finding faults across the whole stack, and explaining a problem plainly to an executive.
How it compares
| Forward-deployed engineer | Staff augmentation | Consultant | |
|---|---|---|---|
| Starts from | Your use case | A CV and a role | A question |
| Where they work | Inside your team or your customer’s, building | Wherever you place them | Mostly advising, from outside |
| Who leads the work | We do | You do | They advise, you decide |
| Who answers for it | We do, for what was agreed | You do | For the advice only |
Is it right for you?
Right for you if
- Your customers take months to go live with your AI product
- Security reviews, data access or integration keep stalling rollouts
- You need an AI engineer now, and a hire would take months
Not the right fit if
- You only need extra hands on work your team already leads: staff augmentation fits better
- There is no defined use case yet: start with the AI and Growth Diagnostic
Related work
Proof
As founding operator and technical lead, our team worked inside enterprise pilots to take a new AI platform from launch to $2.4M in booked annual recurring revenue in 15 months.
Led by our team before Burraq Quantum was formed.
How we work
- Use case first: we work out what the role really needs before we look for anyone.
- Selective: we are as careful about engineers as we are about clients.
- We lead the work: a project lead stays on it and reports to you.
- Not tied to one AI vendor: the engineer uses the model and tools that fit your case.
- The exit is planned from the start: what stays behind is agreed before the work begins.
By sector and city
Riyadh
- FintechAn AI engineer inside your team or your bank customer's in Riyadh, until the AI is in daily use, with one firm accountable for what was agreed.
Questions
Asked about this service
What is a forward-deployed engineer?
An engineer who works inside a business, alongside the people who will use a system, until it is in daily use. They build, adapt and fix on the spot. The role started at Palantir and is now common at AI companies, where the hard part is fitting the product to each customer's data and way of working.
How is this different from staff augmentation?
We start with your use case, not a CV. We work out what the role needs, find and vet the engineer, and put a project lead on the work. You have one agreement with us, and we stay accountable for it.
How is a forward-deployed engineer different from a consultant?
A consultant advises. A forward-deployed engineer builds and ships the working system, inside your team or your customer's, and stays until it runs.
Can the engineer work inside our customer's environment?
Yes. For AI and SaaS companies, the engineer can work with your customer's team to get your product live. How they represent you is agreed in scope before the work starts.
Where do the engineers come from?
From a vetted global network of specialist resourcing partners. We choose the partner and the engineer for each requirement, and we stay your single point of contact throughout.
What if the engineer is not the right fit?
We agree how that is handled before the work starts, as part of the scope. Because we lead the work, we usually see a problem early and deal with it.
What stays behind when the engineer leaves?
Documentation, tests and runbooks, and people on your team trained to run the system. Who owns what is agreed in scope before the work begins.
Should we hire our own AI engineers instead?
If the work is permanent, in time, yes. A forward-deployed engineer gets the AI live now, and can help define the role you later hire for.
Start here
Start witha straightanswer.
A 30-minute call to see whether we can really move your numbers. You leave with a clear next step, even if we never work together.
