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Benchling is an AI platform for biotech R&D used by over 200,000 scientists globally, including major biopharma companies like Sanofi and Moderna. The company is rebuilding biotech for the AI era by combining clean, structured scientific data with AI agents and models integrated into research workflows.
As Product Manager for Schemas, you will own the configuration layer and data-modeling primitives that underpin Benchling's platform. Schemas define how customers model their scientific data and processes—it is the customer-defined data model that makes Benchling different from point solutions and the contract every other system (internal apps, integrations, AI agents) relies on. This is a high-leverage, technically interesting role on the platform team, and the company is investing heavily as AI features increasingly depend on data quality.
Key responsibilities include:
- Set product direction for Schemas and ship incrementally, balancing fast prototyping with platform stability that admins and developers depend on.
- Track how customers use Schemas—where it delights, where it fails—and build sharp personas and job-to-be-done frameworks for each user type (admins, scientists, computational teams, internal and external developers).
- Partner closely with Engineering and Design to ship new capabilities, bringing customer "why" rather than just feature requests.
- Champion structured, well-modeled data as the foundation for AI value across Benchling, anticipating what schema consumers will need next.
- Collaborate with Customer Experience, Field, Sales, and Marketing to get customer signal into the roadmap early.
- Align closely with other Platform and Apps PMs, as schemas underpin nearly every other platform surface.
You will become the go-to person for customers, field teams, and engineers—not a router to engineering. This role requires deep discovery practice, a track record of balancing long-term vision with incremental shipping, and strong communication across technical and executive audiences.
Benchling emphasizes AI fluency as core to how the company works. As part of the interview process, you'll complete a brief AI-focused exercise or discussion.
Flexible hybrid work with expected on-site presence Monday, Tuesday, and Thursday.
QUALIFICATIONS:
- 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.
- Deep, demonstrated discovery practice: has built personas and JTBD frameworks from scratch, not just used ones handed to you.
- 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.
