The profiles nobody can find right now.
AI engineering, security and data. Not three services — three shortages.
Why these three
AI didn’t remove the need for engineers. It concentrated it. Companies hire fewer people than two years ago, and the ones they do hire are harder to find and more expensive to get wrong.
These are the three where that shows up first.
AI engineering
Engineers who connect models and agents to systems that are already in production — and keep them running after the demo. Not people who have read about it: people who have shipped it and watched it fail at 3am.
What they own: integration into real systems · evaluation and guardrails · the part where a prototype becomes something the business can depend on.
Security
Engineers who keep AI adoption from opening a door nobody checked. Every model that touches your data widens the surface — and most teams add the capability faster than they add the review.
What they own: access and data governance around AI systems · review of what the new capability exposes · the controls that let you say yes to adoption.
Data
Engineers who make sure there is something worth feeding all of the above. The most common reason an AI project stalls isn’t the model — it’s that the data underneath it can’t be trusted.
What they own: pipelines, quality and lineage · the layer everything else stands on.
How to check that a partner actually reaches these profiles
Anyone can list three specialties on a page. Ask for the evidence before you sign, not after:
Where have they placed this exact profile, and when?
Not «we work with AI» — which role, which stack, which month.
How many candidates did they see to get there?
A partner that reaches a scarce profile knows their own funnel.
What happens if the person doesn’t work out?
And who absorbs that cost.
Who assessed them technically, and how?
If the answer is a coding test, ask what the test didn’t tell them.
We answer those four in writing. So should anyone else you’re talking to.
What arrives with them
The engineer brings the frameworks and playbooks of ACL and DataArt. Method comes with the person — it doesn’t replace them. Your team gets someone who has a starting point, not someone who has to invent one.
Tell us which profile you need
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