BioTrust Product Engineer San Francisco, CA · Full time Company website

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BioTrust is building the trusted-access layer between frontier AI labs, AI-bio tool developers, gene synthesis providers, and the researchers who use them. We verify once and let researchers be trusted across providers, reducing friction for legitimate science while creating a defensible screening layer against catastrophic misuse. We bring the experience of alumni of the UK AI Security Institute, Microsoft, Asana, the FBI, Los Alamos National Laboratory, and Oxford.

What you'll do

• Build the applications analysts use to research and make verification decisions, owning them end to end from workflow to UX, client and server logic, and data storage.
• Move fast from idea to production: prototype in several directions, get working software in front of analysts quickly, and harden the directions that prove out.
• Work in lock step with analysts as their methodology evolves, understanding the use case deeply and iterating the product alongside them.
• Integrate AI where it earns its place, including calls on local versus cloud models, data separation, privacy, analyst experience, and evals.
• Set technical foundations with the engineering lead and another engineer, including dev loop, testing, deployment practices, and end-to-end architecture.
• Prioritize ruthlessly with the engineering lead, separating rapid MVP milestones from fast follows and future work.

What this job actually looks like

• The codebase is young: prototypes are underway that need to be expanded and hardened into production-grade software. The use case is still being discovered, so requirements shift and the right product is something you'll find by shipping, watching, and iterating rather than by reading a spec.
• Expect a lot of prototyping that won't survive, constant judgment about what's worth hardening, and comfort working in ambiguity close to a high-stakes domain.

What we're looking for

• Strong product instincts and frontend/UX ability.
• A fast, reliable executor across the prototype-to-production loop.
• Strong cross-functional collaboration with non-engineers.
• Senior generalist judgment across the stack.
• Clear, balanced communication through high-stakes trade-offs.
• Comfort getting up to speed on biosecurity and AI risk.

Nice to have

• Depth in systems, data modeling, or infrastructure.
• Experience taking prototypes to production on an early-stage team or greenfield codebase.
• Interest or background in biosecurity, AI safety, or high-stakes trust-and-safety domains.

Other notes

• Compensation will be determined by experience, scope, and impact.