Most companies don’t come to us saying, “we need infrastructure, evaluation, and governance.”
They come saying something simpler.
“We need to hire an Agentic AI Engineer.”
That makes sense on the surface. But when you get closer to what they’re actually trying to do, the problem usually looks very different.
What they really mean is:
“We’ve built something with agents… it sort of works… but we don’t fully trust it, and we don’t know how to get it into production.”
And that’s where hiring starts to go wrong.
The assumption is that the right individual will unlock everything.
A strong hire comes in, builds the system, and takes it live.
In reality, even the best engineers can only go so far if the environment around them isn’t set up properly. We’re seeing people hired to do everything at once — architecture, agents, evaluation, internal tooling, governance — and it quickly becomes unclear what “success” actually looks like.
That’s not a talent issue. It’s a scope issue.
This is where the market is starting to split.
Some companies are still hiring broad, catch-all profiles and hoping one person can cover everything.
Others have stepped back and realised this is a systems problem. They’re thinking more deliberately about how these capabilities are split — who builds, who evaluates, who owns how systems behave in production.
That shift changes how you hire.
It changes the profiles you target.
The strongest candidates right now aren’t just “good with LLMs”. They’ve actually tried to get these systems into production. They understand reliability issues, trade-offs, and how agents behave over time — not just in a demo.
Those profiles are rare, and they don’t always sit under obvious titles.
It also changes how you position the opportunity.
The best people aren’t looking for “another AI role”. They’re looking for real problems, clear intent, and an environment where they can build something that actually gets used.
If a role feels like “come in and figure it all out”, it raises more questions than it answers.
Then there’s competition.
People with genuine agentic AI experience are being pulled in multiple directions — Big Tech, well-funded start-ups, consultancies. If your story isn’t clear, and your process isn’t tight, you lose them.
So where does that leave most companies?
Usually, with roles that feel harder to fill than they should be. Long processes, unclear expectations, and hires that don’t quite land the way they were intended.
The companies moving fastest aren’t just hiring more.
They’re hiring more deliberately.
They understand what they’re building, where the gaps are, and how to structure a team around it. And as a result, they attract better people.
That’s where we come in.
Not just to find individuals, but to shape the thinking behind the hire — what you actually need, where to find it, and how to land it in a competitive market.
Because in this space, hiring isn’t just about filling a role.
It’s about giving that person a real chance to succeed.
Agentic AI is exposing gaps in how companies build technology.
It’s doing the same for how they hire.
The ones that recognise that early are the ones that will actually get this into production — and make it work.