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Build the talent operations function for the AI safety ecosystem that places early-career talent in high-impact roles and connects talent pipelines across orgs.
Note: This role description is a first draft. Scope, salary, and responsibilities may evolve as our plans develop over the coming weeks, and we’ll keep you in the loop about any changes if you apply.
Kairos is a nonprofit accelerating talent into AI safety and policy. In just under two years, we’ve trained over 1000+ people through our flagship programs:
SPAR: The largest AI safety research fellowship, with 400+ mentees per round mentored by researchers from Anthropic, Redwood Research, RAND, MIT, the UK AI Security Institute, and others.
Generator Residency: In partnership with Constellation, a platform for generalist talent to pitch, build, and ship projects that build capacity and infrastructure across the AI safety ecosystem, with advisors from OpenAI, AI Futures Project, METR, and more.
Global Challenges Project: A workshop series introducing promising students to careers in AI safety and biosecurity, run several times a year across Oxford, Boston, and Berkeley.
Pathfinder Fellowship: Helping grow the global network of AI safety university groups from a few dozen to nearly 100, with $1.4M+ in funding to support their work.
We see ourselves as a portfolio of highly impactful projects in a fast-evolving field. By the end of 2027, we expect to double in size and launch several new initiatives addressing critical gaps in the ecosystem.
We’re looking for a Head of Talent Operations to build a new function at Kairos combining internal recruiting, ecosystem headhunting, and a shared talent database for AI safety, Talent Commons. You’d be the first person to own this function, reporting to Neav Topaz (co-director). The role starts by leading hiring across Kairos as we scale from 7 to ~20 people, then expands into the broader ecosystem work as the team grows.
Kairos is scaling fast and we don’t have a dedicated recruiting function. Getting our own hires right is a top priority: every person we bring on has an outsized effect on how fast we can move.
Own Kairos’s hiring pipeline end-to-end. Build and run processes for new roles, drawing on the same networks and judgment you’ll later use for external placement.
Source, evaluate, and close candidates. Manage screening, trial tasks, references, and offers across multiple concurrent searches.
Build hiring infrastructure that lasts. Set up the systems, templates, and rubrics that let Kairos run good hiring rounds without reinventing the process each time.
We have 400+ mentees per round through SPAR and 65+ university organizers through Pathfinder, plus a growing alumni network. 80,000 Hours handles senior headhunting well, but nobody does this for junior talent, and it’s one of the biggest gaps in the ecosystem’s infrastructure.
Build relationships with hiring organizations across the AI safety and policy ecosystem.
Proactively match early-career people from SPAR, Pathfinder, GCP, and the broader network to open roles.
Track placement outcomes and use them to improve the matching process over time.
Turn informal referral work into structured process, so good matches don’t depend on whether someone thinks to ask Neav.
Talent Commons is a shared, consent-based talent database for organizations across the AI safety ecosystem, letting programs like MATS, GovAI, and Horizon surface leads across pipelines. Jesse Gilbert and Agus Covarrubias are building the technical platform, and you’d own the programmatic side.
Onboard partner organizations and get them actually using the platform.
Maintain data quality and the trust that makes the system work.
Shape product direction as the platform develops
Help shape where Kairos goes next. Surface where talent gaps are shifting and what the ecosystem needs.
Work with Neav and Agus on how the function evolves and when to hire into it. We expect this role to grow into a small team, likely in 2027.
This role requires three things in combination: people intuitions (knowing who’s promising, who’s ready, and who belongs where), relationship skills (being someone that hiring orgs and candidates actually want to work with), and a systems orientation (turning good judgment into infrastructure that scales beyond you).
High ownership, strong judgment. You’ll make consequential calls: who’s ready, where to place them, and how to structure the hiring and placement process as it scales. We want someone who can hold that weight and make good decisions without constant check-ins.
Relationship-builder. Headhunting runs on trust. Hiring organizations need to believe your referrals are well-calibrated. Candidates need to feel respected. Partner orgs need to see real value in sharing data and working with you.
Systems thinker. The whole point of this function is to make informal, relationship-dependent work reliable at scale. You should be excited about designing the processes, workflows, and data infrastructure that let good judgment compound.
Mission-aligned. You care deeply about making advanced AI go well and have enough context on the AI safety ecosystem to make good calls about who’s doing valuable work and where the real bottlenecks are.
Direct experience in talent placement, recruiting, or headhunting in AI safety or adjacent spaces
Experience with hiring, selection, or other processes involving high-stakes decisions about people
Existing relationships with organizations in the AI safety ecosystem
You’ll be working toward reducing risks from advanced AI, potentially the most important challenge of our time. Where you place people will directly affect whether organizations working on AI safety get the people they need.
There’s no existing playbook for this function. You’d be designing it and have strong ownership over a large aspect of Kairos’s direction.
You’ll have real strategic input building out Talent Operations and co-creating the strategy with Neav and Agus.
The function will probably grow into a team, and you’d be the natural person to lead it.
We’re building a world-class team, so you’ll be in good company. Work alongside people from METR, Coefficient Giving, Rethink Priorities, and CEA who share your commitment to impact.
Collaborate regularly with leading AI safety researchers, policy professionals, funders, and organizers.
Base salary: $170,000–$230,000, depending on experience and location, with potential for additional compensation for exceptional candidates
Retirement: 10% 401(k) contribution or equivalent pension contribution or salary increase
Location: Access to office space in San Francisco, Berkeley, London, or Boston; optional coworking elsewhere. If you work from an AI safety office in San Francisco, Berkeley, London, or Boston, we cover food, lunches, and office expenses.
Benefits: Flexible working hours, highly competitive health insurance, dental and vision coverage, generous vacation policy, and professional development budget
Team retreats: We host all-team retreats twice a year to connect in person, collaborate, and build team culture.
Start date: Ideally by the end of July 2026
Remote, with expected travel 3-6 times a year for conferences and events, predominantly in the US
We’d also be happy for you to work out of any of the AI safety hubs in San Francisco, Berkeley, London, or Boston, though we have a light preference for people to work out of Berkeley.
We prefer candidates who can attend meetings in the ET time zone (though our team currently spans GMT-8 to GMT+1).
We may be able to provide visa sponsorship to the US, depending on the circumstances (especially, but not exclusively, O-1As).
We’re a small, high-trust team motivated by the urgent challenge of making advanced AI go well. We try hard to figure out where we’re wrong, which means we say uncomfortable things to each other and change our minds fairly often. We value collaborative truth-seeking, a scout mindset, agility, and an alliance mindset with the broader ecosystem.
We also believe meaningful work should be enjoyable. We support each other’s well-being, celebrate wins, and maintain a healthy sense of humor even when the work is hard.
Application form (10–20 mins)
Screening call (15 mins)
Take-home assignment (1.5–3 hours, paid)
Interview (45 mins)
Reference checks
Work trial (3–4 days, paid)
Offer
If you’re excited about this role but unsure whether you meet every qualification, we encourage you to apply anyway.
Questions? Reach out at careers@kairos-project.org.
Know someone who might be a good fit? If your referral gets hired and completes 6 months with us, we’ll pay you a $5,000 referral bonus. Learn more here.
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