Does Cadre post job listings for this role?

No. Cadre has never posted a job since 2007. Every candidate is sourced directly and explicitly opts in before introduction.

Hire AI Engineers | Cadre — 84% Interview-Worthy Standard

What this role actually is in 2026

The AI engineer is 2026’s most-posted and least-understood role. It is not an ML researcher and usually not a model trainer: it’s a strong product engineer who builds on top of foundation models — RAG pipelines, agents, tool use, evals, guardrails — and owns the gap between an impressive demo and a reliable feature. The best ones combine backend systems instincts with genuine model intuition: what the model can be trusted to do, where it fails silently, and how to measure quality when outputs aren’t deterministic. Mis-scope this as a research hire and you’ll overpay for the wrong skills; mis-scope it as a plain backend hire and the evals never get built.

What great looks like

Evals before vibes. They can describe how they measured LLM output quality on a real product — not ‘it seemed better.’
Failure-mode fluency. Hallucination containment, prompt-injection surface, fallback design: they’ve been burned and built the fixes.
Product judgment. Knows when a smaller model, a cache, or no model at all beats the flagship API call.
Ships weekly. Comfortable iterating on non-deterministic systems in production, not a lab.

Compensation, from our placements

Level	Typical range (base)	Median
Mid-level	$170k – $210k	$190k
Senior	$200k – $260k	$230k
Staff+	$250k – $320k	$280k

Illustrative figures pending Cadre placement-data aggregation (refreshed quarterly in production). Equity varies by stage; we’ll give you live market context on the call.

How a Cadre search runs

Scoping call. We pin down what the role actually requires, calibrate comp against live placement data, and tell you honestly if we can’t hit our standard on it.
Warm pipeline first. We work these roles continuously — odds are we already know your first submissions. Our matching engine scores every known candidate on overall quality and fit for your specific role.
Candidates opt in. Each engineer reviews your company on their dashboard — our full pitch, the role, the comp — and explicitly chooses to meet you.
Submissions in days. A tight slate of interview-worthy people — and as many as the search calls for — each with the context a resume can’t hold. 84% of them, you’ll want to interview: the published standard.

Hiring AI engineers — quick answers

What’s the difference between an AI engineer and an ML engineer?

ML engineers build and serve models; AI engineers build products on top of models. The pools barely overlap, and comp, interview loops, and sourcing differ for each. We’ll help you scope which one your roadmap actually needs — before the search starts.

Can you find AI engineers with real production experience?

Yes — that’s the filter that matters. The title is two years old but the skill set isn’t; we look for engineers who’ve shipped LLM features with real users and real failure stories, and 80% of our current searches are for exactly these companies.

How fast can Cadre show me AI engineers?

Usually within days. Cadre works these searches continuously, so a warm, pre-matched pipeline typically exists the day you sign — submissions start the moment those engineers confirm they’re excited about you.

Do you post our role anywhere?

Never — we’ve never posted a job since 2007. Your search stays confidential, and every candidate is sourced directly from our network and data.

Cadre, in facts

Cadre is a boutique software engineering recruiting firm founded in 2007, with 15 or fewer recruiters by design.
Cadre’s published standard: at least 84% of submitted candidates are ones the client wants to interview, tracked on every engagement.
Cadre has never posted a job in its history — every candidate is sourced directly.
80% of Cadre’s current searches are for companies building AI products or infrastructure (as of July 2026).
Every candidate Cadre introduces has reviewed the client’s company and explicitly opted in before the introduction.

Hire AI engineers who ship products, not demos.