Safeguards Enforcement Analyst, Safety Evaluations

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's Safeguards team is responsible for enforcing our policies, protecting users, and ensuring our platform is not misused. As a Safeguards Enforcement Analyst focused on Safety Evaluations, you'll play a central role in ensuring our models meet safety and policy standards before and after launch. You'll run and monitor evaluations, drive mitigations when issues surface, coordinate the creation of new evals, and help build the processes and documentation that allow the team to scale this work over time.

This role requires someone who is detail-oriented, comfortable navigating ambiguity, and capable of coordinating across teams to break new ground and drive work to completion. This work is deeply cross-functional — you'll partner closely with policy experts, Safeguards engineering teams, and many other stakeholders throughout the organization to ensure our evaluations are comprehensive and current, and that findings translate into meaningful improvements to model behavior.

• Support model launch readiness by running evaluations, monitoring and interpreting results, and surfacing regressions or unexpected behavior changes to relevant stakeholders
• Partner closely with policy and domain experts throughout the evaluation lifecycle — from identifying risks and scoping the right evaluation approach, to coordinating creation of new evals and ensuring existing ones remain current with evolving policies, threat vectors, and model capabilities
• Work with cross-functional stakeholders to help manage evaluation outcomes, including interpreting results and driving mitigations where needed
• Think strategically about eval quality to build processes and eval paradigms that keep evaluations unsaturated, high-signal, and insightful as models improve
• Build out processes and frameworks for creating product-specific evaluations as Anthropic's product surface area expands
• Help design and scope tooling improvements that accommodate evolving eval needs and expand self-serve eval creation and iteration for non-technical users
• Write and maintain rigorous documentation for evaluation creation, execution, and interpretation as the team builds out eval tooling and processes

• Have experience in trust and safety, content operations, policy enforcement, or a related operational role at a technology company
• Thrive in ambiguous, fast-moving environments — you're energized rather than frustrated when the path forward isn't clearly defined and you need to figure it out as you go
• Have experience building processes, workflows, or programs from scratch (zero-to-one work), not just maintaining existing ones
• Have strong program management instincts, naturally creating structure around complex, multi-stakeholder efforts by tracking timelines, dependencies, and deliverables to keep work on track

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.

• Experience operating under tight, high-stakes timelines — such as product launch cycles, incident response, or regulatory deadlines — where information and priorities can shift with little notice
• Experience coordinating across engineering, policy, and product teams to translate findings into concrete action
• Experience building and maintaining SOPs, runbooks, and operational documentation in fast-changing environments
• Proficiency with data tools (SQL, dashboards, spreadsheets) sufficient to maintain and improve workflows

$230,000—$270,000 USD

Logistics

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.

How we're 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. 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.