Staff+ Fullstack Software Engineer, Safeguards Engineering

• Design and build the internal review tools analysts use to investigate abuse — dashboards, case queues, and evidence viewers that make high-volume, high-stakes decisions fast and accurate. • Build the interfaces where humans supervise agents: streaming output, interruption and approval flows, and clear provenance for every action an agent takes. • Surface abuse patterns to our research teams through the visualizations and exploration tools that make emerging patterns legible. • Own the frontend architecture for tools handling sensitive data at scale — performance under large datasets, correctness under real-time updates, and access controls enforced end to end.

About Anthropic 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. Note: this job post is for Fullstack Software Engineers only. If you are a Backend Engineer, please see our Backend Software Engineer post here. About the role We are looking for fullstack software engineers to help build safety and oversight mechanisms for our AI systems. As a software engineer on the Safeguards team, you will work to monitor models, prevent misuse, and ensure user well-being. This role will focus on building systems to detect unwanted model behaviors and prevent disallowed use of models. You will apply your technical skills to uphold our principles of safety, transparency, and oversight while enforcing our terms of service and acceptable use policies. We have multiple teams that are currently hiring within Safeguards. Team placement occurs after the interview process, taking into account your interests and experience alongside organizational needs. This flexible approach allows us to match talented engineers where they'll have the greatest impact and growth potential. Responsibilities: • Design and build the internal review tools analysts use to investigate abuse — dashboards, case queues, and evidence viewers that make high-volume, high-stakes decisions fast and accurate. • Build the interfaces where humans supervise agents: streaming output, interruption and approval flows, and clear provenance for every action an agent takes. • Surface abuse patterns to our research teams through the visualizations and exploration tools that make emerging patterns legible. • Own the frontend architecture for tools handling sensitive data at scale — performance under large datasets, correctness under real-time updates, and access controls enforced end to end. You may be a good fit if you have: • A Bachelor’s degree in Computer Science, Software Engineering or comparable experience • Proficiency in TypeScript and modern React; comfortable in Python for backend work • The ability to work across the stack • Strong communication skills and ability to explain complex technical concepts to non-technical stakeholders Strong candidates may also: • 8+ years of experience in a software engineering position, not including internships or co-ops • Have experience building data-dense internal tools or operator interfaces, not just marketing or consumer surfaces • Have experience with integrity, spam, fraud, or abuse detection and mitigation • Have experience building trust and safety detection mechanisms and intervention for AI/ML systems • Have experience with prompt engineering, jailbreak attacks, and other adversarial inputs • Have worked closely with operational teams to build custom internal tooling 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. Annual Salary: $405,000—$485,000 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