About the RoleWe're looking for a Product Manager to shape Rosalind Workbench for life sciences. You will own product strategy and execution, working directly with researchers in academic labs, biotech, and pharma to understand where AI can meaningfully improve their work. You'll partner with engineering, research, design, and customer-facing teams to turn emerging capabilities into intuitive products that scientists return to. This role calls for strong product judgment, depth in life sciences, and the ability to move from an ambiguous research problem to a focused, shippable experience. In this role, you will have the opportunity to define the future of AI guided scientific discovery and build the capabilities and tools that help advance the scientific frontier for researchers and help increase the accessibility of model intelligence for scientific use.
This is a chance to shape how AI shows up in one of the world's most important and complex industries, with enormous room for product innovation, real-world impact, and long-term platform leverage. We move with urgency, hold a high bar for quality and trust, and care deeply about building products that can help improve human health outcomes.
This position is based in San Francisco, CA, with relocation assistance available.
In this role, you will:- Shape Rosalind Workbench's strategy and roadmap, prioritizing high-impact workflows across discovery biology, verification, and CRO management.
- Partner with engineering, research, and design to turn scientific data, tools, and models into intuitive workflows with the depth and control experts need.
- Prototype with Codex, Rosalind Workbench, and GPT-Rosalind to validate ideas with scientists before committing engineering time.
- Partner with Safeguards, Preparedness, Product Policy, and go-to-market teams to build responsible access to scientific capabilities into researcher onboarding and product workflows.
- Drive enterprise readiness for pharma and biotech, spanning data protection, admin controls, research-system integrations, and security, compliance, and procurement requirements.
- Own execution from discovery through launch and iteration, translating user needs and technical constraints into clear requirements and driving adoption with go-to-market partners.
- Build scientific rigor into the experience through reproducible analyses, traceable evidence, visible uncertainty, and scientist review.
- Use product data, researcher feedback, and market insight to improve scientific utility, reliability, adoption, and business impact.
You might thrive in this role if you:- Have a track record of shipping products that solve complex user problems, taking ambitious products from zero to one and scaling adoption or commercial success. Founder experience is a plus.
- Bring substantive life sciences experience through research, industry, or building tools for scientists. You can discuss experimental design, data quality, and biological interpretation with researchers; an advanced degree is helpful, but equivalent practical experience matters.
- Combine strategic judgment with a hands-on builder mindset: prototype ideas, choose focused use cases, and stay close to execution.
- Have built model evaluations or benchmarks, ideally for scientific or agentic workflows, and know how to assess validity, uncertainty, and reliability.
- Can translate between scientists, engineers, designers, and commercial teams. You have the technical fluency to reason about data and tool integrations, model limitations, and the tradeoffs involved in reliable scientific workflows.
- Exercise sound judgment about evidence, uncertainty, privacy, and safety. You know that a convincing output is not sufficient proof of scientific validity, and you build evaluation and expert feedback into product development.
- Have shipped into life sciences, pharma, or regulated research environments and understand data governance, compliance, and responsible access to sensitive capabilities.
- Care deeply about helping scientists make discoveries. You combine curiosity and user empathy with a high bar for usability, and are motivated to make advanced AI useful across the realities of everyday research.
