Aimed at mid-to-senior level engineering leaders who manage complex products and work across scientific domains.
Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from Openai via Ashby
ABOUT THE TEAM
Life sciences is one of the clearest areas where advances in intelligence can meaningfully benefit the world at large. 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. Rosalind Workbench can be used with any OpenAI models including GPT-Rosalind, our dedicated life sciences model, which combines frontier reasoning with specialized tool orchestration across medicinal chemistry, genomics, wet-lab assistance, and other scientific applications. Our long term vision is for teams of agents to work together across these domains, giving researchers access to broader expertise and the ability to pursue more ambitious scientific questions.
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. You should be comfortable reviewing architecture and code, investigating difficult failures, and helping engineers make consequential technical decisions. You’ll work closely with product, design, research, Codex engineering, and customer-facing teams to bring new scientific capabilities into everyday use.
IN THIS ROLE, YOU WILL
- Build and lead the engineering team. Hire strong engineers, coach technical leaders, provide clear feedback, and establish ownership and accountability across product and infrastructure work.
- Drive technical planning and delivery. Translate scientific and customer needs into scoped milestones. Make explicit tradeoffs, resolve dependencies, and keep a small team focused as the product and research agenda evolve.
- Shape the Workbench architecture. Guide development across scientific interfaces, agent and tool orchestration, local and remote compute, durable execution, and persistent project state. Build shared components that support new scientific workflows.
- Make scientific work inspectable and reproducible. Preserve the inputs, versions, results, and decisions behind an analysis. Ensure scientists can move between conversations, viewers, and follow-up investigations without losing context or control.
- Own engineering quality in production. Establish testing, release practices, observability, and an effective on-call process. Improve workflow reliability, latency, and cost, and lead resolution of problems that prevent scientists from completing their work.
- Coordinate across teams and partners. Align with Codex on shared platform capabilities and with customer-facing engineers on deployment needs. Lead technical decisions about building or integrating scientific tools, specialist models, data sources, and experimental service providers.
- Turn customer learning into reusable improvements. Work directly with scientists and design partners to understand their workflows. Address enterprise requirements such as private compute, credentials, networking, permissions, and data handling, with clear ownership for common product improvements and customer-specific integrations.
- Connect product engineering with research. Help turn capabilities proven in internal research into supported product features. Build instrumentation and feedback pipelines that measure successful workflows and repeat use, and support evaluation and model improvement under explicit consent and data-use requirements.
- Build safety and trust into the product. Partner with security, privacy, and safety teams to implement appropriate access controls, review points, auditability, and retention policies throughout scientific workflows.
YOU MIGHT THRIVE IN THIS ROLE IF YOU
- Have experience managing engineering teams that ship and operate complex software products.
- Bring strong software engineering fundamentals and the technical judgment to work across user-facing applications, backend services, data systems, and compute infrastructure.
- Have helped turn early prototypes or research capabilities into reliable products used by external customers.
- Can create clarity in ambiguous situations, communicate technical decisions plainly, and coordinate teams with different priorities and reporting structures.
- Care deeply about product usability and can translate expert workflows into software that users can understand, inspect, and trust.
- Build teams where engineers take ownership, learn quickly, and maintain high standards while shipping.
- Are motivated by scientific discovery and willing to learn closely from scientists and domain experts.
PARTICULARLY RELEVANT EXPERIENCE
- 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, customer-managed infrastructure, and organizational access controls.
- Developer platforms that let users build, validate, and share reusable tools or workflows.
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
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Source: Openai careers (Ashby)