Engineering Manager, Agent Prompts & Evals

About Anthropic

Anthropics 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.

About the Role

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. Its a platform team whose platform is model behavior itself.

The team sits deliberately at the seam between product engineering and research. Youll 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 dont 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 whos built strong platform or devtools teams before and is excited to apply that skillset to a domain where the thing youre measuring is a language model.

Responsibilities

• 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 Claudes 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 the API and agentic surfaces

• Be a steady hand through model launches these are the teams 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

You May Be a Good Fit If You Have

• 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 dont 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

Strong Candidates May Also Have

• 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

Logistics

Minimum education: Bachelors 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 arent 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 youre interested in this work. We think AI systems like the ones were 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 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 youre ever unsure about a communication dont click any linksvisit for confirmed position openings.

How were different

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. Were 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.

Come work with us!

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 aboutour policyfor using AI in our application process