Product Manager, Platform

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.

• 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).
• Bring customer "why," not just feature requests, back to Engineering and Design; partner with them closely to ship new capabilities.
• Champion structured, well-modeled data as the foundation for AI value across Benchling, anticipating what schema consumers will need next.
• Partner with Customer Experience, Field, Sales, and Marketing to get customer signal into the roadmap early.
• Partner closely with other Platform and Apps PMs — schemas underpin nearly every other platform surface, so alignment on sequencing and shared abstractions matters as much as your own roadmap.
• Energized by platform work and systems thinking; comfortable building the right abstraction ahead of need.
• Has designed, owned, or significantly evolved a data-modeling, schema, or configuration system used by external developers or technical admins — not just consumed one as a feature.
• Becomes the go-to person for customers, field, and engineers — not a router to engineering.
• Deep, demonstrated discovery practice: has built personas and JTBD frameworks from scratch, not just used ones handed to them.
• Track record balancing long-term vision with incremental shipping.
• Strong communicator across technical and executive audiences; B2B SaaS or developer-platform background preferred.
• Genuine curiosity about the science behind the data. You don't need a science background, but you should want one by the end of your first quarter here.

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