Product Manager, Platform

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.

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.