Product Manager, Platform

About this role

We are rebuilding biotech for the AI era. When a breakthrough is delayed, the world waits. Getting a molecule from discovery to patients, or a crop from lab to field, involves thousands of slow, manual, disconnected steps. AI has the potential to change this, compressing decades of R&D work into years. But that only happens when clean, structured scientific data and AI are built into how science gets done. Benchling is the AI platform for biotech R&D.

Scientists use Benchling to design experiments, capture structured data, and run AI agents and models directly in their workflows. Over 200,000 scientists around the world trust Benchling to power their most important work, from academic labs to Sanofi, Moderna, and more than half of the world's top 50 biopharma. We’re building an AI scientist for our customers. We can’t do that if we haven’t built the muscle ourselves.

AI fluency is the foundation we build on; it's core to how we work, and we're committed to helping every new hire integrate it into their day-to-day. As part of our interview process, you'll complete a brief AI-focused exercise or discussion so we can understand how you think about and use AI to drive impact in your role. Feel free to reference any tools, platforms, or workflows you use today. ROLE OVERVIEW AI is only as good as the data underneath it.

Schemas is the configuration layer where customers model their scientific data and processes. It's the customer-defined data model that makes Benchling different from a point solution, and the contract every other system (internal apps, integrations, AI agents) relies on when reading or writing to Benchling. Get it right, and AI inherits a solid foundation; get it wrong, every layer above inherits the problem. As Schemas PM, you own the primitives (schema types, computed fields, fieldsets, constraints, static properties, data versioning) that every other team at Benchling builds on top of.

This is one of the highest-leverage, most technically interesting roles on the platform team, and one we're investing in now as AI features across Benchling increasingly depend on the quality of the underlying data model. RESPONSIBILITIES - Set product direction for Schemas and ship toward it incrementally, balancing fast prototyping with the platform stability admins and developers depend on. - Relentlessly track how customers use Schemas — where it delights, where it fails — and build sharp personas and job-to-be-done context for each user type (admins, scientists, computational teams, internal and external developers).