Technical Sourcer

The Context

Hi, I'm Logan, and I lead Talent at Alembic. I want to tell you about the hardest search we run, because it's the one you'd own first. Alembic's science team implements causal mathematics — the algorithms our whole product rests on — directly in CUDA and C++. The people who can do this work are engineers who went and got a PhD, or PhDs who then engineered for years. They are not on the first page of any LinkedIn search. They're in labs, HPC groups, quant shops, and PhD-exit communities, and most of them aren't looking. Finding and genuinely engaging them is a research problem, a writing problem, and a craft problem all at once. If that paragraph excited you rather than tired you, you're who I'm looking for.

The wider context: a $145M Series B, a company expecting to roughly double in the next year, and a hiring plan that's mostly technical. Sourcing is the bottleneck on the hardest of those searches, which makes this seat one of the highest-leverage in the company.

How we work, briefly: structured hiring with scorecards before searches; speed as our competitive advantage; an operating loop of Learn → Build → Share → Repeat; and an AI-native practice — we experiment with new sourcing tools constantly and expect to find alpha before our competitors do. We wrote our playbook down before we wrote this ad, and we share it openly here.