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Engineering Manager, Rosalind Workbench

Hybrid

Part remote, part office, you need to live within commuting distance of a named location.

Hybrid · San Francisco

Employer listed it 4 weeks ago · Added 2 weeks ago

Been open since 4 weeks ago, still being checked, but it has been live a while.

Salary

$401k to $536k per year

Location

Hybrid · San Francisco

Timezone

Not stated

Contract

Full-time

Experience

Mid

Category

Software

Published by the employer

What the advert says

Quoted word for word from the employer's advert. Where it says nothing, we say so.

Working hours
Not mentioned in the advert
Where you can work from
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…
Contract
Not mentioned in the advert
Experience asked for
Not mentioned in the advert
Pay
Not mentioned in the advert

Remote flexibility

Hybrid

This role is only partly remote, the employer expects time in the office around San Francisco, Hybrid, so you need to live within commuting distance.

What the employer says

  • Source listing states candidate location: "San Francisco, Hybrid"
  • Listing mentions "Hybrid"

What Nomaders makes of it

  • Not suitable if you plan to move between countries

The quotes above are the employer's own words; the reading is ours. Always check the original listing and employment terms before working from another country.

Before you apply

Experience: employer states

Written as a requirement

  • “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.”

Questions worth asking: Nomaders interpretation

  • This role involves office time, but the advert does not say how often. Ask how many days a week are expected on site.
  • The advert does not say whether this is employment or a contractor arrangement. Ask, as it affects tax and benefits.

Produced automatically from this advert's text; not reviewed by a person. The employer's own page is the final word.

About the role

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.

Requirements

The employer hasn't listed requirements separately, they're described in the role summary above and on the original listing.

Benefits

No benefits package published with this listing. Ask about it at first interview.

How to apply

  1. 1Check the flexibility label above, hybrid, matches where you plan to live and work.
  2. 2Tailor your CV to the role at OpenAI, mentioning your remote working experience.
  3. 3Apply directly on the employer's careers page using the button below. Nomaders never handles your application.

Found 17d ago. Last checked today. Always confirm the details on the original posting, salary and location can change after publication.

Listing sourced from Company boards.

$401k to $536k per year · You'll be taken to the employer's careers page.