AI.
Heads of AI, VP Machine Learning, Directors of Applied Research, Principal AI/ML Engineers. Recruiters who can credibly engage senior AI candidates.
Senior AI talent moves on conviction, not on listings.
The Head of AI you actually want is not on a job board. They are deciding between two competing offers from operators they already know. The recruiter has to be able to make a credible case in technical specifics: the data, the model, the deployment, the autonomy, and the scientific roadmap.
Engaged search funds that depth. The recruiter assigned has experience placing AI leadership across both AI-native companies and traditional enterprises that are building their first AI organization. Outreach is targeted, technical, and discreet.
We work AI-native companies (foundation models, AI products, AI infrastructure), enterprises building their first AI org, AI-applying SaaS, and AI-research-adjacent operators (academia/industry hybrids).
Why Platforms Choose Engaged Search
Where the search lives.
Senior leadership and niche-headhunter roles. The recruiter assigned to your search has spent a decade in this segment.
AI LEADERSHIP
RESEARCH LEADERSHIP
SENIOR IC
AI PRODUCT & PLATFORM
AI, specifically.
The questions hiring operators send in the first call.
What kinds of AI roles do you recruit for?
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AI leadership (Head of AI, VP ML, CAO), research leadership (Directors of Applied Research, VP Research), senior individual contributors (Principal AI/ML Engineers, Distinguished Engineers), and AI product/platform (VP AI Product, Heads of AI Platform, MLOps).
Do you place candidates from major research labs?
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Yes. Senior AI candidates from major research labs and frontier-AI operators are a recurring engagement. The recruiter assigned has experience scoping for the publication, autonomy, and compute realities those candidates expect.
Are AI searches typically engaged or contingent?
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Senior leadership searches are engaged. Senior IC searches run engaged or contingent depending on the candidate-pool depth and the comp band.
Do you understand the difference between research-led and product-led AI orgs?
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Yes. The two organizational models attract different candidates and run different motions. Research-led AI orgs need leaders who can run a publication-and-compute strategy; product-led AI orgs need leaders who can ship to customer-facing latency budgets. The recruiter assigned scopes for both contexts.
Do you cover the entire United States?
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Yes. AI roles are predominantly remote or in major metro areas (Bay Area, NYC, Boston, Seattle, Austin); the recruiter assigned has experience placing across geographies.
Three paths from here.
You're hiring a Head of AI or VP ML Engineering.
Engaged search fits, the candidate pool is small, mostly passive, and concentrated in 4-5 metros plus remote. We map the pool in five days.
Start the scoping call →You're scoping the role and unsure whether to hire research-led or applied-led.
Read the AI in Executive Search post for the working-session framework, it surfaces which type of leader fits your product surface.
Read the AI search framework →You're benchmarking AI engineering comp before the offer.
Send us the candidate's prior employer and current band. We come back with a peer-firm comp read inside one business day.
Email the read request →Tell us the model, the team, the role.
We connect you with AI research and product leaders who understand your compute environment, model architecture, and scientific roadmap. We deliver verified shortlists in 30 days.