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Your work will directly support Anthropic&#39;s mission to develop AI systems that are safe, beneficial, and trustworthy.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Design, build, and operate distributed backend systems that power secure sandboxed execution environments</li>\n<li>Scale infrastructure to meet growing research and product demands while maintaining reliability and performance</li>\n<li>Implement and maintain serverless architectures and container orchestration systems</li>\n<li>Collaborate with research teams to understand requirements and translate them into robust infrastructure solutions</li>\n<li>Develop monitoring, alerting, and observability systems to ensure operational excellence</li>\n<li>Participate in on-call rotations and incident response to maintain system reliability</li>\n<li>Contribute to infrastructure automation and tooling that improves developer productivity</li>\n<li>Partner with security teams to ensure sandboxing infrastructure maintains appropriate isolation guarantees</li>\n</ul>\n<p>You may be a good fit if you:</p>\n<ul>\n<li>Have 5+ years of experience building and operating backend infrastructure at scale</li>\n<li>Have deep expertise in distributed systems design and implementation</li>\n<li>Have strong operational experience, including debugging complex production issues</li>\n<li>Are proficient with cloud platforms, particularly GCP/GCS (experience with AWS or Azure is also valuable)</li>\n<li>Have experience with containerization technologies (Docker, Kubernetes) and understand their security implications</li>\n<li>Are comfortable working with infrastructure as code and modern DevOps practices</li>\n<li>Have strong programming skills in languages such as Python, Go, or Rust</li>\n<li>Are results-oriented with a bias towards flexibility and impact</li>\n<li>Care about the societal impacts of your work and are motivated by Anthropic&#39;s mission</li>\n</ul>\n<p>Strong candidates may also have experience with:</p>\n<ul>\n<li>Serverless architectures and functions-as-a-service platforms (Cloud Functions, Cloud Run, Lambda)</li>\n<li>Designing and implementing secure multi-tenant systems</li>\n<li>High-performance computing environments or ML infrastructure</li>\n<li>Linux systems internals, including namespaces, cgroups, and seccomp</li>\n<li>Network security and isolation techniques</li>\n<li>Building systems that support research workflows and rapid iteration</li>\n</ul>\n<p>The annual compensation range for this role is $300,000-$405,000 USD.</p>\n<p>We encourage you to apply even if you do not believe you meet every single qualification. 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We define the authentication architecture for our training infrastructure, design the cryptographic foundations that protect model weights and training data, and drive the developer security program that shapes how engineers build and ship software.</p>\n<p><strong>About the role:</strong></p>\n<ul>\n<li>Scope, design, and build complex security systems end to end, maintaining them through production and driving through ambiguous technical challenges with minimal oversight</li>\n<li>Identify systematic risks through threat modeling and risk assessment, then build the controls and infrastructure that address them</li>\n<li>Mentor engineers across the security team and broader engineering organisation, contribute to hiring, and grow security engineering culture at Anthropic</li>\n<li>Enable other teams to build their own security solutions by providing design pattern guidance and expanding security ownership beyond the security team</li>\n</ul>\n<p><strong>Developer security and supply 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Your work will directly support Anthropic&#39;s mission to develop AI systems that are safe, beneficial, and trustworthy.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Design, build, and operate distributed backend systems that power secure sandboxed execution environments</li>\n<li>Scale infrastructure to meet growing research and product demands while maintaining reliability and performance</li>\n<li>Implement and maintain serverless architectures and container orchestration systems</li>\n<li>Collaborate with research teams to understand requirements and translate them into robust infrastructure solutions</li>\n<li>Develop monitoring, alerting, and observability systems to ensure operational excellence</li>\n<li>Participate in on-call rotations and incident response to maintain system reliability</li>\n<li>Contribute to infrastructure automation and tooling that improves developer productivity</li>\n<li>Partner with security teams to ensure sandboxing infrastructure maintains appropriate isolation guarantees</li>\n</ul>\n<p><strong>You may be a good fit if you</strong></p>\n<ul>\n<li>Have 5+ years of experience building and operating backend infrastructure at scale</li>\n<li>Have deep expertise in distributed systems design and implementation</li>\n<li>Have strong operational experience, including debugging complex production issues</li>\n<li>Are proficient with cloud platforms, particularly GCP/GCS (experience with AWS or Azure is also valuable)</li>\n<li>Have experience with containerization technologies (Docker, Kubernetes) and understand their security implications</li>\n<li>Are comfortable working with infrastructure as code and modern DevOps practices</li>\n<li>Have strong programming skills in languages such as Python, Go, or Rust</li>\n<li>Are results-oriented with a bias towards flexibility and impact</li>\n<li>Care about the societal impacts of your work and are motivated by Anthropic&#39;s mission</li>\n</ul>\n<p><strong>Strong candidates may also have experience with</strong></p>\n<ul>\n<li>Serverless architectures and functions-as-a-service platforms (Cloud Functions, Cloud Run, Lambda)</li>\n<li>Designing and implementing secure multi-tenant systems</li>\n<li>High-performance computing environments or ML infrastructure</li>\n<li>Linux systems internals, including namespaces, cgroups, and seccomp</li>\n<li>Network security and isolation techniques</li>\n<li>Building systems that support research workflows and rapid iteration</li>\n</ul>\n<p><strong>Logistics</strong></p>\n<p><strong>Education requirements:</strong> We require at least a Bachelor&#39;s degree in a related field or equivalent experience. <strong>Location-based hybrid policy:</strong> 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.</p>\n<p><strong>Visa sponsorship</strong></p>\n<p>We do sponsor visas! However, we aren&#39;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.</p>\n<p><strong>We encourage you to apply even if you do not believe you meet every single qualification.</strong></p>\n<p>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&#39;re interested in this work.</p>\n<p><strong>Your safety matters to us.</strong></p>\n<p>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&#39;re ever unsure about a communication, don&#39;t click any links—visit anthropic.com/careers directly for confirmed position openings.</p>\n<p><strong>How we&#39;re different</strong></p>\n<p>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. 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