Talent Intelligence Lead

As a Talent Intelligence Lead, you are the front of the funnel for our hardest searches. The candidates we place often cannot be found on LinkedIn alone. They are the strongest engineer in a small open-source project, a postdoc whose name appears on a frontier paper, a builder whose best proof of work is a repository rather than a resume. Your job is to find them before anyone else does, map the pool from scratch, and hand the team a calibrated, well-researched slate. This is not list-pulling. It is original research. You will become genuinely fluent in technical talent markets and learn to recognize quality from primary signals, not titles. What you will do: Build candidate universes from zero for each mandate. No database recycling. Source from primary channels most recruiters never touch: GitHub contributor graphs, arXiv and OpenReview author lists, conference proceedings, technical Discords and communities, lab and research-group rosters, and the networks of known top performers. Learn to read strong-hire signals directly from the work. Sustained, substantive contribution history. Meaningful pull requests into core projects rather than cosmetic ones. Demos that actually run. The ability to ship a brand new idea within weeks. Maintain clean, structured candidate maps and pipelines in our ATS so the whole pod works from one source of truth. Write short, sharp candidate briefs that explain why a person fits the bar, with the evidence attached. Partner closely with recruiters and the principal on calibration, so the bar sharpens with every search. What you bring: 1 to 3 years in sourcing, recruiting research, technical talent research, or a comparable analytical role. Strong new graduates with real proof of independent research will be considered. Genuine curiosity about deep tech. You do not need to be an engineer, but you should be able to learn what makes one credible and enjoy doing so. Sharp pattern recognition and a researcher's instinct for following a thread. Disciplined, organized, and comfortable owning data hygiene in a shared system. Clear writing. You can explain why a candidate matters in a few honest sentences. Nice to have: Familiarity with GitHub, arXiv, or technical communities from the inside. Exposure to an ATS (we use modern tooling) and to AI-native research workflows. A technical or scientific background, or a track record of teaching yourself hard subjects quickly. #J-18808-Ljbffr Azimuth Partners