Your investors' talent team, dedicated to your search.
VC funds have in-house recruiters — but they're spread across hundreds of portfolio companies. We bring the same network access and cap-table judgment, focused entirely on your hire.
Founding AI Engineer
Three ways to hire. One that actually reaches them.
Contingency recruiters send volume. AI sourcing tools stop at the top of the funnel. Your investors' own talent team is stretched across a hundred portfolio companies. We're one dedicated team with portfolio access and cap-table judgment — pointed entirely at your search.
Portfolio-grade access.
We recruit from inside our investors' portfolios — not cold-calling from the outside. That means candidates who aren't on the market — and a warm path to the ones who are.
Investor perspective.
We read cap tables, model equity outcomes, and workshop offers. Recruiting with founder-level context — the difference between a "maybe" and a signed offer.
Judgment you can't automate.
An embedded search partner who knows the candidates, understands the cap table, and closes with founder-level context.
Calibrate the real hire
We diagnose what the role actually needs — not a job description, the signal.
Work the network
We call people we know — and people who trust the people we know. Relationships, not databases.
Warm intros & references
Warm intros over spray-and-pray. Reference-backed signal before you invest time.
Founder-vetted shortlists
Founders see 3–5 people per search — each vetted through conversations and references, not keyword filters.
Close with investor context
Equity, leveling, comp — we help you frame the offer that actually closes.
What founders say.
Real outcomes from real searches. No aggregated testimonials, no names we can't share.
How the best AI companies get built.
Simile, Explained
A Stanford paper turned into a company — then sold by the field force of the category it replaces. Fifty-nine people, $300M at a $2B valuation, and 26 who sell or deploy against 23 who build.
Periodic Labs, Explained
A frontier-AI research crew, a robotic chemistry lab and $605M — aimed at one material that doesn’t exist yet. Seventy-one people hired in the order the bets required: bits in 2025, atoms in 2026.
The Barbell Company — Moonlake AI
Three olympiad champions and a 25-year NVIDIA Distinguished Engineer in the same 30-person startup — and just 4 of the 31 profiles we read are anywhere near the middle of their career.
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Talent teardowns, comp signals, and how the best AI startups actually build their teams. New reports as we publish them — no spam, unsubscribe anytime.