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San Francisco, California, United States
Hybrid
Available
We are building Watcher, a coding agent security product. Watcher is deployed in production and monitors billions of agent tokens per month across engineering teams at agent-building scale-ups and multinational enterprises. We are now hiring our first dedicated Engineering Manager to lead the product engineering team.
We are looking for a strong hand-on engineer who still ships code, and can own both the people management and the execution of the product engineering team. This is a player-coach role. Today, you will spend most of your time managing and coordinating, but still ship code. As the team grows, you’ll transition towards 100% leadership and management.
The team is small today and is growing fast, so you will have significant say in shaping the team, the process, and the product, and your scope will grow with the team. You will report directly to Marius (CEO), who will own Watcher’s product direction and roadmap.
Own the team's planning and tracking. Turn goals and customer commitments into concrete, well-scoped tickets with clear owners. Everyone on the team should always know what they're supposed to be doing and whether we're on track.
Run the operating rhythm (planning, standups or async equivalents, retros).
Track dependencies between product engineering, monitoring research, and infrastructure/security work, and proactively resolve conflicts.
Translate between researchers and product engineers. Turn research outputs (new monitors, backtesting results) into scoped, prioritized engineering work.
Track customer commitments (integration timelines, requested features, incident follow-ups) and coordinate releases, testing, documentation, and customer communication.
Surface risks and slippage early, and proactively give Marius (CEO) an accurate, always-current picture of status.
Directly manage the product engineers. Run regular 1on1s, give direct and actionable feedback, and own their growth, performance, and wellbeing.
Own performance management end to end. Set clear expectations, recognize strong work, and address underperformance early and honestly.
Drive hiring for the team. Own the pipeline together with ops, run interview loops, close candidates, and onboard new engineers so they ship in their first weeks.
Protect the team's focus. Shield engineers from thrash, keep meetings minimal, and make sure priorities are stable enough to execute against.
Ship code yourself. Features, bug fixes, internal tooling, and prototypes, primarily in Python and TypeScript. Staying hands-on keeps your technical judgment current and your tickets realistic.
Set the technical bar, make architecture decisions, review code and establish norms, and release and incident processes.
Build tooling that makes the team faster, including AI-assisted tooling for your own job (status reporting, ticket triage, ramp-up docs). We expect you to leverage AI heavily when reasonable across both management and engineering work.
Lead the team within 90 days. For the first few weeks, you will work closely with all engineers to understand their priorities, all of our ways of working, and procedures. Then, we ramp up responsibilities and you start to scope out proposals and get rapid and detailed feedback. Once you have onboarded properly, you will start running the meetings, etc.
Deliver a major customer integration. Scope a large enterprise deployment with the team, turn it into tickets, sequence it against other priorities, track progress against the customer's timeline, and ship code on the critical path yourself where needed.
Scale the team. Scope the hiring needs for the next 2-3 product engineers, drive the process end to end, while keeping the existing team shipping. Ensure hiring is done to a high standard and is fast.
Bridge a research handoff. Take a new monitoring capability from the research team, work with researchers and engineers to turn it into a scoped production plan, and manage its delivery into Watcher including rollout, documentation, and customer-facing changes
Strong engineering background. You worked as a software engineer for at least 4 years before managing. You still ship production code today. You will be judged partly on code you write in this role, primarily in Python and/or TypeScript.
People management experience. You have hired, onboarded and managed small teams of engineers directly (1on1s, feedback, performance,), or you have been a tech lead who de facto did this for at least 2 years. You can point to engineers who grew or shipped better because of you.
Execution ownership. You have run delivery for a multi-person engineering effort, turning goals into tickets, tracking them to completion, and being accountable for the outcome.
High agency. You see what the team needs and do it without being asked, whether that's fixing a process, having a hard conversation, or shipping the fix yourself.
Direct communication. You give and take blunt feedback, address problems with people early and kindly, and say clearly when something is off track, including to the CEO.
Startup pace. You are excited about a fast-moving environment, comfortable with ambiguity and changing priorities, and willing to grind when it matters.
Comfortable leveraging AI heavily for management, coordination, and coding work, while holding the output to a high standard. You have used Claude Code, Codex, Cursor, or similar tools heavily.
Experience coordinating between research and engineering, or shipping products with an ML/research component.
Customer-facing delivery experience, e.g. enterprise integrations, deployment projects, or technical account work.
Formal AI safety background. We need excellent engineering leaders who can learn the AI safety context.
Large-team management experience. This is a small, senior team. Managing 30 people at a big company is neither necessary nor necessarily good preparation.
Certifications (PMP, scrum, etc.). We care about demonstrated ability, not credentials. If your instinct is the heavyweight process, this is the wrong team.
This role offers market competitive salary, equity, and competitive benefits.
Salary: San Francisco: $283,000 - $396,000; London: £190,000 - £266,000
Our engineers effectively have an unlimited token budget. If a better result costs more compute, use it.
Flexible work hours and schedule
Unlimited vacation
Unlimited sick leave
Up to 6 months of paid parental leave
Comprehensive health, dental and vision insurance
Retirement savings with competitive employer matching (e.g. 401(k) for US employees)
Lunch, dinner, and snacks are provided for all employees on workdays
Paid work trips, including staff retreats, business trips, and relevant conferences
A yearly $1,000 (USD) professional development budget
Relocation support and visa fees (if applicable)
Time Allocation: Full-time
Location: This is an in-person role working out of our London or San Francisco office. We offer flexible working hours and some wfh arrangements.
Visa sponsorship: We sponsor visas in both the UK and US. Sponsorship isn't guaranteed for every role or candidate, but if we make you an offer, we'll work with you to find the right visa route.
The product team consists of product engineers: Jeremy Neiman, Zak Walters, Zen van Riel, Srdjan Miletic and Gustavo Bicalho; research scientists: Victor Gillioz, Monika Jotautaitė, Dmitrii Volkov; and our GTM lead: Kyle Dai. Marius Hobbhahn (CEO) advises the team. Furthermore you will interact with our other SWEs and researchers, since we intend to be "our own customer" by using our products internally for our research work. You can find our full team here.
The rapid rise in AI capabilities offers tremendous opportunities, but also presents significant risks. At Apollo Research, we're primarily concerned with risks from Loss of Control, i.e. risks coming from the model itself rather than e.g. humans misusing the AI. We're particularly concerned with deceptive alignment / scheming, a phenomenon where a model appears to be aligned but is, in fact, misaligned and capable of evading human oversight.
We work on the science of scheming, detection of scheming (e.g. building evaluations), and scheming mitigations (e.g. anti-scheming). We also work on control and monitoring research (see our scalable monitoring agenda). We work closely with many frontier AI companies, such as OpenAI, Anthropic, Google, Meta, Thinking Machines and others, e.g. to test their models and collaborate on the science of scheming. At Apollo, we aim for a culture that emphasizes truth-seeking, being goal-oriented, giving and receiving constructive feedback, and being friendly and helpful. If you're interested in more details about what it's like working at Apollo, you can find more information here.
We also build a coding agent security product called Watcher that secures agent deployments in companies. Our goal is to reduce the probability of catastrophic incidents by securing coding agents, learning about their real-world risks, and publishing our research on how to build these control systems most effectively.
Equality Statement: Apollo Research is an Equal Opportunity Employer. We value diversity and are committed to providing equal opportunities to all, regardless of age, disability, gender reassignment, marriage and civil partnership, pregnancy and maternity, race, religion or belief, sex, or sexual orientation.
Please complete the application form with your CV. The provision of a cover letter is neither required nor encouraged. Please also feel free to share links to relevant work samples.
About the interview process: Our multi-stage process includes a screening interview, a take-home test (approx. 3 hours), 3 technical interviews, and a final interview with Marius (CEO). There are no leetcode-style general coding interviews. You may use AI tools on the take-home; we judge the result the way we'd judge any contributor's work, so you are responsible for the quality of everything you submit. If you want to prepare, we suggest building simple monitors for coding agents and running them on your own Claude Code / Cursor / Codex / etc. traffic.
Your Privacy and Fairness in Our Recruitment Process: We are committed to protecting your data, ensuring fairness, and adhering to workplace fairness principles in our recruitment process. To enhance hiring efficiency, we use AI-powered tools to assist with tasks such as resume screening. These tools are designed and deployed in compliance with internationally recognized AI governance frameworks. Your personal data is handled securely and transparently. All resumes are screened by a human and final hiring decisions are made by our team. If you have questions about how your data is processed or wish to report concerns about fairness, please contact us at info@apolloresearch.ai.
