AI writes the code.
It still doesn’t understand your business.
Making AI work inside your business takes an engineer who learns how your business runs. We find that engineer for you.
What this is
We fill a technical position on your team with a professional working from another country.
A professional joins your team and works inside it: your standups, your repository, your priorities. We employ them in the country where they live. This arrangement answers the two questions most companies ask first: who carries the legal and payroll obligations, and who decides what gets built.
We are their legal employer.
Payroll, compliance, and employment obligations sit with us, in the country where the engineer lives.
You direct the work.
Architecture, code review, and product decisions stay with your engineering leaders. You keep the project, and we fill the position.
Ways to fill the role
Three ways to work with us. Choose the one that fits your team.
Each one fits a different situation:
- Your team knows the role and the skills it needs, but can’t find the person.
- You want the same work done by fewer people over time, with AI handling the repetitive part.
- You prefer to pay less up front and tie part of the fee to results.
The engineers and the employment model are the same in all three. What changes is how you pay and how we share the risk with you. You can start with one model and move to another later.
Staff augmentation: for a role you’ve already defined
You tell us the role, the skills, and the start date. We find the engineer, employ them in their country, and your team directs the work.
AI-augmented teams: more output with a smaller team
A team that starts with six engineers and is designed to shrink to two, as what they learn becomes documentation, tests, and tools your team keeps.
Outcome-based engagement: part of the fee tied to results
You pay less up front. The rest depends on the targets we agree on, measured at the end of the period, so we share part of the risk with you.
The profiles nobody can find right now
AI concentrated the demand for engineers in three profiles.
Generic roles became easier to fill and harder to justify. These three moved the other way: they are scarcer, more senior, and much more expensive to leave open. A vacancy in any of them can stall a roadmap. These are the profiles we specialize in.
The questions you’re already asking
Who legally employs them, and what does that put on me?
Legal employer →What risk stays with me, no matter who I hire through?
Risk and liability →How do I assess someone my team can’t interview in depth?
Technical assessment →How long does it take, and what does the wait cost?
Scarce profiles and time to fill →How our engineers work
Framework-equipped talent.
Our engineers arrive with the engineering frameworks and playbooks of the ACL group: how code is reviewed, how access is granted, how data is handled, and which data an engineer may share with an AI model.
That saves time at the start. Your engineer doesn’t have to build review, access, and data practices from scratch, so the first weeks go into learning your systems and your business.
It also covers something companies often ask about too late. An engineer who already works within a security and compliance discipline won’t improvise one on your systems. With AI in the toolchain, this matters more: a model with access to your data is a risk someone has to control. Our engineers arrive with those rules already written and refined across 30+ years and 200+ companies, several of them in regulated industries.
A proven method behind every engineer.
30+
years
7,000+
engineers hired
200+
companies
25
technical recruiters
From the blog
Tell us which position you can’t fill.
Tell us about the role. We’ll tell you which profile fits, how long the search usually takes, and what remains your responsibility.
