at Anthropic
Location
San Francisco, CA | New York City, NY
Compensation
$320k–$405k USD
Type
full time
Posted
3 months ago
Remote
Yes
Market range · function + seniority
p25 · target · p75 · n=187
Posted $405k · well above market
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Free account · ATS keyword check · per-job bullet rewrite by Claude.
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
Anthropic is looking for an Engineering Manager to lead the Agent Prompts & Evals team. This team owns the infrastructure that lets Anthropic ship model and prompt changes with confidence — the eval frameworks, system prompt pipelines, and regression-detection systems that every model launch depends on.
When a new Claude model is ready to ship, this team is the one answering “is it actually better in our products?” When a product team wants to change how Claude behaves, this team owns the tooling that tells them whether they broke something. It’s a platform team whose platform is model behavior itself.
The team sits deliberately at the seam between product engineering and research. You’ll partner closely with other evals groups across the company on shared infrastructure and methodology, with product teams who are shipping features on top of Claude, and with the TPMs and research PMs driving model launches. The pace is set by the model release cadence, and the team operates as both a platform owner and a hands-on partner during launch periods.
You don’t need a research background, but you do need to want to learn how to measure things like “is Claude being too sycophantic” or “did web search get worse.” The best version of this role is someone who’s built strong platform or devtools teams before and is excited to apply that skillset to a domain where the thing you’re measuring is a language model.
Lead and grow a team of prompt engineers and platform software engineers
Own the product-side eval platform: the frameworks, dashboards, bulk runners, and CI integrations that product teams use to measure Claude’s behavior and catch regressions before they ship
Own system prompt infrastructure: versioning, deployment, rollback, and review tooling for the prompts that run in production across claude.ai, the API, and agentic surfaces
Be a steady hand through model launches — these are the team’s highest-stakes operational moments and the EM is the backstop when things get chaotic
Build durable collaboration with other evals groups across the company; this means real work on ownership boundaries, shared roadmaps, and avoiding tragedy-of-the-commons on shared eval infrastructure
Recruit, close, and retain engineers who want to work at the intersection of product engineering and model behavior
Shape where the team invests next: there are credible paths into frontier eval development, model launch automation, and deeper prompt engineering support, and part of the job is sequencing them
Push the team toward measuring things that are hard to measure — behavioral drift, prompt quality, harness parity — not just things that are easy
8+ years in software engineering with 3+ years managing engineering teams, including experience leading a platform, infra, or developer-tooling team where your customers were other engineers
A track record of building “pits of success” — tooling and process that made it easy for other teams to do the right thing without needing to understand all the details
Comfort managing a team with a mixed charter: platform ownership, service-to-other-teams, and a launch-driven operational rhythm, all at once
Enough technical depth to engage on system design, review pipeline architecture, and be credible in debates with strong ICs — you don’t need to be writing code by hand every day, but you should be able to read it, review it, and be comfortable leveraging Claude to understand, design, and occasionally build.
A product mindset and willingness to wear multiple hats when the work calls for it
Demonstrated ability to build and maintain peer relationships with partner orgs that have different cultures and incentives — negotiating ownership, aligning roadmaps, and holding ground when it matters without being territorial about it
Experience recruiting and closing senior ICs in a competitive market
Prior exposure to LLM evals, ML experimentation platforms, or model quality work — even tangentially
Experience with A/B testing infrastructure, feature flagging, or gradual rollout systems
Background in devtools, CI/CD platforms, or testing infrastructure at scale
A history of managing teams that sit between two larger orgs and making that position an asset rather than a liability
Interest in AI safety and alignment — not required, but it makes the “why” of the work land harder
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
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