Today we’re launching the a16z Talent Engineer Fellowship: an 8-week cohort for the people building the next operating system for recruiting.
Here’s the problem. AI has made every part of recruiting noisier at exactly the moment companies need sharper signal. Resumes are easier to polish. Inbound is harder to parse. Outbound is easier to spam. And the best candidates, more in demand than ever, have mostly stopped looking.
The old recruiting stack still matters: better sourcing, better process, better relationships, better closing. But it no longer differentiates, because everyone now has the same tools. The advantage is shifting to teams that build their own.
Sales already went through this. When Clay and its cousins arrived, a new role emerged — the GTM engineer — and the companies that figured it out early ran circles around everyone still grinding through manual SDR work. Recruiting is at the same inflection point right now.
We call the role that comes out the other side the Talent Engineer.
What Is a Talent Engineer?
A talent engineer is an engineer who recruits — not just a recruiter who codes.
The distinction matters. This isn’t a recruiter using AI tools, it’s not a recruiting-ops person keeping the ATS clean. It’s the person who gives companies like Cursor, OpenAI, xAI, Ramp their unfair advantage in finding the best people fastest, building systems to identify/attract top talent.
You’ve probably met the proto version. Every good startup has one: the engineer who never had the title, may not have reported into recruiting, shipped real code — and somehow ran the technical screens, interviewed half the company, and got everyone’s best referrals. They were doing talent engineering before there was a name for it.
What they build: sourcing agents, market maps, relationship graphs, candidate-intelligence workflows, referral systems that actually work, AI-assisted technical evaluations, hiring-manager context engines, talent-brand surfaces, and the weird internal tools that make the whole machine smarter.
What they understand: that recruiting, done right, isn’t an assessment problem. It’s a many-to-many matchmaking problem — the right person, the right role, the right moment — and matchmaking is an engineering problem.
If this sounds like you, apply here by July 24. Applications are rolling, and the fellowship begins in late August.
How It Works
8 weeks, starting late August.
Time commitment is flexible — everything is opt-in
What You’ll Get
A tight network of ~40 AI-native talent leaders, recruiting systems-builders, and talent-infrastructure founders
An in-person dinner series in SF, expanding to more cities by demand
Demos, live working sessions, and honest feedback on what you’re building
Off-the-record conversation about what’s actually working in sourcing, candidate intelligence, evaluation, referrals, and closing
Access to the a16z ecosystem — including founders trying to hire for roles that don’t have names yet
Who You’ll Be Joining
You’ll break bread with founding fellows and industry leaders like:
Viet Nguyen - Founder @ Talent Collective, prev. Dir of Recruiting @ Vercel
Dan McCarthy - Senior Talent Engineer @ Zapier
Jared Long - Recruiting Ops Lead @ Cursor, prev. Head of Recruiting Systems, Operations, and Analytics @ OpenAI
Jeffrey Li - CTO @ Paraform
Madison Morales - Talent @ Anthropic, prev. Talent @ General Catalyst
Sebastian Cuadros - Head of Talent Engineering @ Fonzi AI
Amit Matani - CEO @ Wellfound, founded AngelList Talent @ AngelList
Johnny Sanchez - Head of Recruiting Operations & Technology @ Airbnb
Danielle Poreh - Clay for Recruiting Lead (prev. Talent Scientist) @ Clay
Scott Bianco - Head of Talent @ Hebbia
Umesh Khanna - Talent Engineering Lead @ xAI
Joshua Gill - Talent Engineering & Operations @ Luma AI
…and many more.
Why a Fellowship
Because the people doing this work are learning faster than any playbook can keep up.
Right now, one team is building sourcing agents. Another is mapping hidden talent pools from social data. Another has redesigned candidate evaluation around live AI-assisted work sessions instead of leetcode. Another turned referrals and backchannels into a real system instead of a pile of Slack messages. Another is building talent-brand surfaces that make exceptional people raise their hand before they’re looking.
Almost all of this knowledge is trapped inside individual teams.
We want to put these builders in the same room: trade notes, demo what they’re building, pressure-test the edge cases — and define what Talent Engineering becomes before the market settles into worse language.
And with all that’s possible to build, the best people in the world won’t engage with an automated screen, and tooling without judgment is just spam with better infrastructure. The talent engineers worth knowing understand that the system exists to earn the human conversation, not replace it. That sensibility is a requirement here, not a nice-to-have.
We’re Looking for Fellows Who:
Have built or instrumented part of the recruiting workflow themselves — sourcing, screening, evaluation, or anything downstream in the talent stack
Are engineers who run technical screens and think systematically about how to read candidate quality at scale
Have real talent judgment: taste for non-obvious people, role fit, timing, and candidate experience
Operate AI-first, with evidence they’re using modern systems in the work rather than just talking about them
Can turn messy recruiting judgment into workflows, agents, dashboards, interview loops, enrichment systems, or relationship graphs
Care enough about trust and candidate experience that better tooling makes the work better, not just louder
Would make the strongest people in the room feel like they’d met a peer.
You may not call yourself a talent engineer. Maybe you’re an engineering leader, a sourcer, a recruiter, a people-analytics builder, a talent-infrastructure founder, or something that doesn’t have a title yet. Titles matter less than what you’ve built — the work speaks for itself.
If that’s you, apply here. We’re accepting applications on a rolling basis.
Questions? Email [email protected].
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