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OpenAI's Life Sciences team is building Rosalind Workbench, a central environment that brings together scientific tools, data sources, interactive biology file viewers, and core life sciences workflows to help scientists accelerate research. The platform integrates with GPT-Rosalind, OpenAI's dedicated life sciences model, which combines frontier reasoning with specialized tool orchestration across medicinal chemistry, genomics, wet-lab assistance, and other scientific applications. The long-term vision is for teams of agents to work together across domains, enabling researchers to pursue more ambitious scientific questions.
You will lead the engineering team building Rosalind Workbench and its supporting infrastructure. This is a hands-on leadership role where you'll hire and develop engineers, set technical direction, and translate an ambitious product roadmap into focused, reliable releases. You'll review architecture and code, investigate difficult failures, and help engineers make consequential technical decisions.
Key responsibilities include: building and leading the engineering team with clear hiring, coaching, and accountability; driving technical planning and delivery by translating scientific and customer needs into scoped milestones; shaping the Workbench architecture across scientific interfaces, agent and tool orchestration, compute infrastructure, and persistent project state; ensuring scientific work is inspectable and reproducible by preserving inputs, versions, results, and decisions; owning engineering quality in production through testing, release practices, observability, and on-call processes; coordinating across teams including Codex and customer-facing engineers; turning customer learning into reusable improvements while addressing enterprise requirements like private compute and data handling; connecting product engineering with research to turn proven capabilities into supported features; and building safety and trust into the product through appropriate access controls and data-use policies.
You'll work closely with product, design, research, Codex engineering, and customer-facing teams to bring new scientific capabilities into everyday use.
QUALIFICATIONS & RELEVANT EXPERIENCE:
- Experience managing engineering teams that ship and operate complex software products
- Strong software engineering fundamentals and technical judgment across user-facing applications, backend services, data systems, and compute infrastructure
- Track record of turning early prototypes or research capabilities into reliable products used by external customers
- Ability to create clarity in ambiguous situations, communicate technical decisions plainly, and coordinate teams with different priorities and reporting structures
- Deep care for product usability and ability to translate expert workflows into software that users can understand, inspect, and trust
- Demonstrated ability to build teams where engineers take ownership, learn quickly, and maintain high standards while shipping
- Motivation by scientific discovery and willingness to learn closely from scientists and domain experts
Particularly relevant experience includes: scientific software, computational biology, bioinformatics, chemistry, or laboratory workflows; AI agents, model inference, tool integrations, or evaluation infrastructure; workflow orchestration, long-running jobs, reproducible computation, or artifact versioning; enterprise software deployed with private data and organizational access controls; and developer platforms that let users build, validate, and share reusable tools or workflows.
