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  <jobs>
    <job>
      <externalid>6f3a053e-c43</externalid>
      <Title>Staff Software Engineer, AI Reliability Engineering</Title>
      <Description><![CDATA[<p>We&#39;re seeking a Staff Software Engineer to join our AI Reliability Engineering team. As a key member of our team, you will develop Service Level Objectives for large language model serving systems, design and implement monitoring and observability systems, and lead incident response for critical AI services.</p>
<p>You will work closely with teams across Anthropic to improve reliability across our most critical serving paths. You will be responsible for making the systems that deliver Claude more robust and resilient, whether during an incident or collaborating on projects.</p>
<p>To be successful in this role, you should have strong distributed systems, infrastructure, or reliability backgrounds. You should be curious and brave, comfortable jumping into unfamiliar systems during an incident and helping drive resolution even when you don&#39;t have deep expertise yet.</p>
<p>You will be working on high-availability serving infrastructure across multiple regions and cloud providers. You will support the reliability of safeguard model serving, which is critical for both site reliability and Anthropic&#39;s safety commitments.</p>
<p>If you&#39;re committed to creating reliable, interpretable, and steerable AI systems, and you&#39;re passionate about working on complex technical problems, we&#39;d love to hear from you.</p>
<p style="margin-top:24px;font-size:13px;color:#666;">XML job scraping automation by <a href="https://yubhub.co">YubHub</a></p>]]></Description>
      <Jobtype>full-time</Jobtype>
      <Experiencelevel>staff</Experiencelevel>
      <Workarrangement>hybrid</Workarrangement>
      <Salaryrange>€235.000-€295.000 EUR</Salaryrange>
      <Skills>distributed systems, infrastructure, reliability, Service Level Objectives, monitoring, observability, incident response, high-availability serving infrastructure, cloud providers, SRE, Production Engineer, chaos engineering, systematic resilience testing, AI-specific observability tools and frameworks, ML hardware accelerators, RDMA, InfiniBand</Skills>
      <Category>Engineering</Category>
      <Industry>Technology</Industry>
      <Employername>Anthropic</Employername>
      <Employerlogo>https://logos.yubhub.co/anthropic.com.png</Employerlogo>
      <Employerdescription>Anthropic is a public benefit corporation that creates reliable, interpretable, and steerable AI systems.</Employerdescription>
      <Employerwebsite>https://www.anthropic.com/</Employerwebsite>
      <Compensationcurrency></Compensationcurrency>
      <Compensationmin></Compensationmin>
      <Compensationmax></Compensationmax>
      <Applyto>https://job-boards.greenhouse.io/anthropic/jobs/5101169008</Applyto>
      <Location>Dublin, IE</Location>
      <Country></Country>
      <Postedate>2026-04-18</Postedate>
    </job>
    <job>
      <externalid>709b405a-48b</externalid>
      <Title>Staff / Senior Software Engineer, AI Reliability</Title>
      <Description><![CDATA[<p>We&#39;re seeking a Staff / Senior Software Engineer, AI Reliability to join our team. As a key member of our AIRE (AI Reliability Engineering) team, you will partner with teams across Anthropic to improve reliability across our most critical serving paths. You will develop Service Level Objectives for large language model serving systems, design and implement monitoring and observability systems, assist in the design and implementation of high-availability serving infrastructure, lead incident response for critical AI services, and support the reliability of safeguard model serving.</p>
<p>You may be a good fit for this role if you have strong distributed systems, infrastructure, or reliability backgrounds, are curious and brave, think holistically about how systems compose and where the seams are, can build lasting relationships across teams, care about users and feel ownership over outcomes, have excellent communication and collaboration skills, and bring diverse experience.</p>
<p>Strong candidates may also have experience operating large-scale model serving or training infrastructure, experience with one or more ML hardware accelerators, understanding of ML-specific networking optimizations, expertise in AI-specific observability tools and frameworks, experience with chaos engineering and systematic resilience testing, and contributions to open-source infrastructure or ML tooling.</p>
<p>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. We value impact and believe that the highest-impact AI research will be big science. We work as a single cohesive team on just a few large-scale research efforts and value communication skills.</p>
<p>If you&#39;re interested in this role, please submit an application even if you don&#39;t believe you meet every single qualification. We encourage diversity and strive to include a range of diverse perspectives on our team.</p>
<p style="margin-top:24px;font-size:13px;color:#666;">XML job scraping automation by <a href="https://yubhub.co">YubHub</a></p>]]></Description>
      <Jobtype>full-time</Jobtype>
      <Experiencelevel>staff</Experiencelevel>
      <Workarrangement>hybrid</Workarrangement>
      <Salaryrange>$325,000-$485,000 USD</Salaryrange>
      <Skills>distributed systems, infrastructure, reliability, Service Level Objectives, monitoring and observability systems, high-availability serving infrastructure, incident response, safeguard model serving, large-scale model serving or training infrastructure, ML hardware accelerators, ML-specific networking optimizations, AI-specific observability tools and frameworks, chaos engineering and systematic resilience testing, open-source infrastructure or ML tooling</Skills>
      <Category>Engineering</Category>
      <Industry>Technology</Industry>
      <Employername>Anthropic</Employername>
      <Employerlogo>https://logos.yubhub.co/anthropic.com.png</Employerlogo>
      <Employerdescription>Anthropic is a public benefit corporation that creates reliable, interpretable, and steerable AI systems.</Employerdescription>
      <Employerwebsite>https://www.anthropic.com/</Employerwebsite>
      <Compensationcurrency></Compensationcurrency>
      <Compensationmin></Compensationmin>
      <Compensationmax></Compensationmax>
      <Applyto>https://job-boards.greenhouse.io/anthropic/jobs/5113224008</Applyto>
      <Location>San Francisco, CA | New York City, NY | Seattle, WA</Location>
      <Country></Country>
      <Postedate>2026-04-18</Postedate>
    </job>
    <job>
      <externalid>c930b80e-7a6</externalid>
      <Title>Staff / Senior Software Engineer, AI Reliability</Title>
      <Description><![CDATA[<p><strong>About Anthropic</strong></p>
<p>Anthropic&#39;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.</p>
<p><strong>About the Role</strong></p>
<p>AIRE (AI Reliability Engineering) partners with teams across Anthropic to improve reliability across our most critical serving paths -- every hop from the SDK through our network, API layers, serving infrastructure, and accelerators and back. We jump into the trenches alongside partner teams to make the systems that deliver Claude more robust and resilient, be it during an incident or collaborating on projects.</p>
<p>Reliability here is an emergent phenomenon that transcends any single team&#39;s boundaries, so someone has to zoom out and look at the whole picture. That&#39;s us -- and it means few teams at Anthropic offer this kind of dynamic, cross-cutting exposure to the systems that matter most.</p>
<p>Claude has your back. AIRE has Claude&#39;s. Help us keep Claude reliable for everyone who depends on it.</p>
<p><strong>Responsibilities:</strong></p>
<ul>
<li>Develop appropriate Service Level Objectives for large language model serving systems, balancing availability and latency with development velocity.</li>
</ul>
<ul>
<li>Design and implement monitoring and observability systems across the token path.</li>
</ul>
<ul>
<li>Assist in the design and implementation of high-availability serving infrastructure across multiple regions and cloud providers</li>
</ul>
<ul>
<li>Lead incident response for critical AI services, ensuring rapid recovery, thorough incident reviews, and systematic improvements.</li>
</ul>
<ul>
<li>Support the reliability of safeguard model serving -- critical for both site reliability and Anthropic&#39;s safety commitments.</li>
</ul>
<p><strong>You may be a good fit if you:</strong></p>
<ul>
<li>Have strong distributed systems, infrastructure, or reliability backgrounds -- we&#39;re looking for reliability-minded software engineers and SREs.</li>
</ul>
<ul>
<li>Are curious and brave -- comfortable jumping into unfamiliar systems during an incident and helping drive resolution even when you don&#39;t have deep expertise yet.</li>
</ul>
<ul>
<li>Think holistically about how systems compose and where the seams are.</li>
</ul>
<ul>
<li>Can build lasting relationships across teams -- our engagement model depends on being welcomed as teammates, not outsiders with opinions.</li>
</ul>
<ul>
<li>Care about users and feel ownership over outcomes, even for systems you don&#39;t own.</li>
</ul>
<ul>
<li>Have excellent communication and collaboration skills -- you&#39;ll be partnering across the entire company.</li>
</ul>
<ul>
<li>Bring diverse experience -- the team&#39;s strength comes from people who&#39;ve built product stacks, scaled databases, run massive distributed systems, and everything in between.</li>
</ul>
<p><strong>Strong candidates may also:</strong></p>
<ul>
<li>Have been an SRE, Production Engineer, or in similar reliability-focused roles on large scale systems</li>
</ul>
<ul>
<li>Have experience operating large-scale model serving or training infrastructure (&gt;1000 GPUs).</li>
</ul>
<ul>
<li>Have experience with one or more ML hardware accelerators (GPUs, TPUs, Trainium).</li>
</ul>
<ul>
<li>Understand ML-specific networking optimizations like RDMA and InfiniBand.</li>
</ul>
<ul>
<li>Have expertise in AI-specific observability tools and frameworks.</li>
</ul>
<ul>
<li>Have experience with chaos engineering and systematic resilience testing.</li>
</ul>
<ul>
<li>Have contributed to open-source infrastructure or ML tooling.</li>
</ul>
<p><strong>Logistics</strong></p>
<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>
<p><strong>Visa sponsorship:</strong> 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>
<p><strong>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&#39;re interested in this work.</strong></p>
<p><strong>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&#39;re ever unsure about a communication, don&#39;t click any links—visit anthropic.com/careers directly for confirmed position openings.</strong></p>
<p><strong>How we&#39;re different</strong></p>
<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 a team sport, where everyone contributes to the overall success of the team.</p>
<p style="margin-top:24px;font-size:13px;color:#666;">XML job scraping automation by <a href="https://yubhub.co">YubHub</a></p>]]></Description>
      <Jobtype>full-time</Jobtype>
      <Experiencelevel>staff</Experiencelevel>
      <Workarrangement>hybrid</Workarrangement>
      <Salaryrange>$325,000 - $485,000 USD</Salaryrange>
      <Skills>distributed systems, infrastructure, reliability, large language model serving systems, monitoring and observability systems, high-availability serving infrastructure, incident response, safeguard model serving, SRE, Production Engineer, ML hardware accelerators, ML-specific networking optimizations, AI-specific observability tools and frameworks, chaos engineering, systematic resilience testing, open-source infrastructure or ML tooling</Skills>
      <Category>Engineering</Category>
      <Industry>Technology</Industry>
      <Employername>Anthropic</Employername>
      <Employerlogo>https://logos.yubhub.co/anthropic.com.png</Employerlogo>
      <Employerdescription>Anthropic is a company that creates reliable, interpretable, and steerable AI systems. It has a quickly growing team of researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.</Employerdescription>
      <Employerwebsite>https://job-boards.greenhouse.io</Employerwebsite>
      <Compensationcurrency></Compensationcurrency>
      <Compensationmin></Compensationmin>
      <Compensationmax></Compensationmax>
      <Applyto>https://job-boards.greenhouse.io/anthropic/jobs/5113224008</Applyto>
      <Location>San Francisco, CA | New York City, NY | Seattle, WA</Location>
      <Country></Country>
      <Postedate>2026-03-08</Postedate>
    </job>
  </jobs>
</source>