Headhunting Product Specialist

Summary 80,000 Hours’ headhunting team helps organisations working to safely navigate the transition to transformative AI find the people they need. We have an AI-powered headhunting service to do this: hiring managers tell us about a role and what they’re looking for, and our AI system searches our database of 16,000+ candidates to produce an initial list of potential fits. A human headhunter then refines the results based on the hiring manager’s feedback. Since 2025, our service has helped place more than 40 people in impactful opportunities. Last quarter, hiring managers reached out more than 2,000 times to candidates we suggested, across 187 searches for 79 organisations. We’re receiving more search requests than we can handle, and many of the organisations we serve are planning to scale their hiring over the next 1–2 years. As such, we’re hiring a Headhunting Product Specialist to help us meet this demand. This role involves running some searches each quarter, where you'll talk to hiring managers and find the top candidates in our database with the help of large language models (LLMs). Your main focus, though, will be improving our product and processes, such as experimenting with different search approaches, doing data analysis, and suggesting or making product improvements. We’re looking for people with good judgment in assessing people’s fit for a role, familiarity with using LLMs, and a track record of getting things done. Previous experience with product development or recruiting is not required; we care more about finding a good generalist with a good understanding of some of our priority problems . Location: London, San Francisco Bay Area, or Washington DC preferred, though we’re open to remote candidates who can overlap for a few hours with UK/US time zones. Salary: Based on experience and location, ranges from £93k–109k (London), $151k-176k (San Francisco), $133k–155k (Washington DC), $116k–135k (US remote), and £81k–94k (other remote) Deadline: Apply by 11:00 PM BST on September 2, 2026 . Applications will be assessed on a rolling basis, so we recommend applying early. We’re also hiring for Headhunting Associates/Specialists who will focus on running searches. You can find more details on that role here , and you can choose to apply for it as well via the same application form. About the team and opportunity 80,000 Hours provides free career support to people working on the world’s most pressing problems , particularly helping society navigate a transition to a world with transformative AI . The headhunting team helps organisations working on these problems find the people they need. We do this mainly through an AI-powered service that assists with the “sourcing” stage of hiring, i.e. finding good candidates to hire and inviting them to either apply or suggest someone else who could be a good fit. AI has changed how much sourcing work a small headhunting team can do. Our system can search thousands of candidates far faster than a human could, allowing headhunters to focus on understanding what hiring managers need and surfacing the strongest leads. And we think the ceiling will keep rising. As AI capabilities advance, existing organisations are expanding, new ones are forming, and the stakes are drawing more people towards work on making sure advanced AI goes well for the world. At the same time, LLMs are becoming more capable of matching those people to the right opportunities. Each of these trends makes the others more valuable. We're receiving more search requests than we can handle, and many of the organisations we serve are planning to scale their hiring over the next 1–2 years. We also think the product has a lot of headroom: today's models could already do much more for us than our current system gets out of them. Improvements here are unusually leveraged, since a better search process improves every search we run, and a better experience for hiring managers means more of them use us. This role exists to capture that upside. What the role is like This role includes running searches and improving our product, with more of your time going to the latter. Running a search typically looks like: Having a 15–30 minute call with the hiring manager to better understand what types of leads they’re looking for, and/or reading their feedback on the first list we sent. Using our Claude skills to generate and tweak rubrics to assess a candidate’s fit for the role. You’ll then look at the top 100–300 leads per search and filter these down to the leads worth sending, along with any other leads that you think might be a good fit. Working on product improvements could look like: Testing different rubrics on searches we’ve done before that have the hiring manager’s feedback, and seeing which rubrics lead to more calibrated lists Testing different models on a search and seeing which ones lead to better results Writing about what roles a candidate may be interested in or a good fit for based on their profile to improve future searches Doing data analysis with the help of LLMs, such as on which searches got better feedback and which organisations we are more able to help Doing user interviews with hiring managers, reading feedback, and suggesting overall improvements to the product (Optionally) Prototyping and/or shipping new product features with the help of LLMs You’ll report to either Brian Tan or Huw Thomas and work closely with the rest of the headhunting team. You may also collaborate with other teams, such as our advising, job board, and AI products teams. This is a full-time role. The start date is flexible, though we’d like the person we hire to start as soon as possible. What success looks like in your first 12 months By the end of your first year, we’d expect you to: Have helped place multiple people into impactful opportunities through your searches or product improvements. Have tested multiple approaches to improving our processes and product , written clear write-ups about the results, and helped implement the best ones. Own one or more areas of the headhunting team’s work, such as deciding which searches we should prioritise, being the lead for experiments, or prioritising which features to build for a certain product area. What we’re looking for You’ll enjoy this work and do it well if you have most of the following: Have good judgment in assessing people’s fit for a role . You can look at a candidate’s LinkedIn/CV and make quick decisions about whether to suggest them to a hiring manager. Have a good understanding of some of the organisations that we serve, such as some of the organisations on our job board . You can talk to a hiring manager, understand their focus areas and team culture, and figure out what types of profiles they might want. Are a competent user of LLMs. You use LLMs regularly already and can give them the right context and instructions to do useful work for you. Have high agency and a track record of getting things done. You've run something without much direction before, whether a project, a team, or a company. You make sensible calls when the right answer isn't obvious, and you don't drop balls. Are intellectually curious . You’re genuinely interested in understanding why some searches succeed and others fail. Are good at reasoning and communicating clearly . You can reason through problems well, identify the crux of disagreements, express yourself clearly and precisely, and demonstrate a high level of reasoning transparency . You might be especially well-suited if you have one or more of the following: Have existing networks in one or more fields relevant to making transformative AI go well, e.g. AI safety, AI governance, biosecurity, other emerging challenges , and/or field-building roles that support these areas Have experience with or near hiring decisions (either in recruiting or as a hiring manager) Have product development experience (e.g. in product management, user experience design, software engineering, or data analysis) Are a power user of AI tools, such as Claude Cowork/Code or OpenAI’s Codex Are based in or willing to move to the Bay Area, Washington DC, or London, where many of the organisations we serve operate. We don’t expect any one person to be equally strong in every dimension, and we encourage you to apply even if you don’t meet every criterion. Salary and benefits Salaries at 80,000 Hours are set using a salary calculator visible to all staff that accounts for the specific role, location, and a candidate's experience. For this role, we expect it to range from £93k–109k for London-based staff, $151k-176k for San Francisco-based staff, $133k–155k for DC-based staff, $116k–135k for US remote staff, and £81k–94k for other remote staff. We can support both UK and US visa sponsorship, but we cannot guarantee US visa applications will be successful. You can read more about the US visa types we can sponsor here , and make a call on whether you’d still like to apply if that is your only location option. Our benefits include: 25 days of paid holiday, plus public holidays Private medical insurance Long-term disability insurance Pension scheme / retirement plan with employer contributions Up to 14 weeks of fully paid parental leave and childcare allowance for children under five £5,000 annual mental health support allowance £5,000 annual self-development budget The option to use 10% of your time for self-development Gym, shower facilities, and unlimited free food at our London office How to apply Apply by 11:00 PM BST on September 2, 2026 . We'll be reviewing applications as they come in and begin assessing candidates as soon as some have met the bar. The application process is likely to include a work test, 1–2 interviews, and a multi-day assessment (preferably in person). We pay for work tests and the multi-day assessment, conditional on location and right to work in the country where you are taking the assessment. We know factors like gender, race, and socioeconomic background can affect people's willingness to apply for roles where they meet many but not all the suggested attributes. We especially encourage people from underrepresented backgrounds to apply, even if you don't meet every criterion.