Description
Compensation
The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The salary range for this position is $401K - $536K per year, with additional compensation including generous equity, performance-related bonuses, and benefits.
Benefits
- Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts
- Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)
- 401(k) retirement plan with employer match
- Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)
- Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees
- 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time
- Mental health and wellness support
- Employer-paid basic life and disability coverage
- Annual learning and development stipend to fuel your professional growth
- Daily meals in our offices, and meal delivery credits as eligible
- Relocation support for eligible employees
- Additional taxable fringe benefits, such as charitable donation matching and wellness stipends
About the team
The OpenAI Life Sciences team works at the intersection of advancing frontier life sciences model capabilities and building products to help scientists accelerate their research and leverage the full potential of AI for scientific work. Rosalind Workbench brings together the scientific tools, data sources, interactive biology file viewers, and core life sciences workflows into a central environment to help scientists investigate questions, design experiments, analyze results, and advance discovery.
About the role
We're looking for an Engineering Manager to lead the team building Rosalind Workbench and its supporting infrastructure. You'll hire and develop engineers, set technical direction, and turn an ambitious product roadmap into focused, reliable releases. This is a hands-on leadership role, requiring comfort with reviewing architecture and code, investigating difficult failures, and helping engineers make consequential technical decisions.
Responsibilities
- Build and lead the engineering team, hiring strong engineers, coaching technical leaders, and establishing ownership and accountability
- Drive technical planning and delivery, translating scientific and customer needs into scoped milestones
- Shape the Workbench architecture, guiding development across scientific interfaces, agent and tool orchestration, and compute infrastructure
- Make scientific work inspectable and reproducible, preserving inputs, versions, results, and decisions behind an analysis
- Own engineering quality in production, establishing testing, release practices, observability, and an effective on-call process
- Coordinate across teams and partners, aligning with Codex on shared platform capabilities and with customer-facing engineers on deployment needs
- Turn customer learning into reusable improvements, working directly with scientists and design partners to understand their workflows
- Connect product engineering with research, helping turn capabilities proven in internal research into supported product features
- Build safety and trust into the product, partnering with security, privacy, and safety teams to implement access controls and auditability
Requirements
- Experience managing engineering teams that ship and operate complex software products
- Strong software engineering fundamentals and technical judgment to work across user-facing applications, backend services, data systems, and compute infrastructure
- Ability to create clarity in ambiguous situations, communicate technical decisions plainly, and coordinate teams with different priorities and reporting structures
- Motivation by scientific discovery and willingness to learn closely from scientists and domain experts
Nice to have
- Experience with scientific software, computational biology, bioinformatics, chemistry, or laboratory workflows
- Familiarity with AI agents, model inference, tool integrations, or evaluation infrastructure
- Knowledge of workflow orchestration, long-running jobs, reproducible computation, or artifact versioning
- Experience with enterprise software deployed with private data, customer-managed infrastructure, and organizational access controls