You will work across the full infrastructure stack, from cloud platforms and networking to application-level performance, and will bridge the gap between high-level research needs and low-level hardware constraints to build the most efficient AI infrastructure in the world. You will help with building the telemetry, cost attribution, and optimization frameworks that ensure every dollar of our infrastructure investment delivers maximum value.

Responsibilities:

• Build and evolve telemetry and monitoring systems to provide deep visibility into infrastructure performance, utilization, and costs across our cloud and datacenter fleets.

• Design and implement cost attribution frameworks for our multi-tenant infrastructure, enabling teams to understand and optimize their resource consumption.

• Identify and resolve performance bottlenecks and capacity hotspots through deep analysis of distributed systems at scale.

• Partner closely with cloud service providers and internal stakeholders to optimize cluster configurations, workload placement, and resource utilization across AI training and inference workloads,including large-scale clusters spanning thousands to hundreds of thousands of machines.

• Develop and champion engineering practices around efficiency, driving a culture of performance awareness and cost-conscious design across Anthropic.

• Collaborate with research and product teams to deeply understand their infrastructure needs, and design solutions that balance performance with cost efficiency.

• Drive architectural improvements and code-level optimizations across multiple services and platforms to deliver measurable utilization and performance gains.

You may be a good fit if you:

• Have 6+ years of relevant industry experience, 1+ year leading large scale, complex projects or teams as a software engineer or tech lead

• Deep expertise in distributed systems at scale, with a strong focus on infrastructure reliability, scalability, and continuous improvement.

• Strong proficiency in at least one programming language (e.g., Python, Rust, Go, Java)

• Hands-on experience with cloud infrastructure, including Kubernetes, Infrastructure as Code, and major cloud providers such as AWS or GCP.

• Experience optimizing end-to-end performance of distributed systems, including workload right-sizing and resource utilization tuning.

• You possess a deep curiosity for how things work under the hood and have a proven ability to work independently to solve opaque performance issues

• Experience designing or working with performance and utilization monitoring tools in large-scale, distributed environments.

• Strong problem-solving skills with the ability to work independently and navigate ambiguity.

• Excellent communication and collaboration skills,you will work closely with internal and external stakeholders to build consensus and drive projects forward.

Strong candidates may have:

• Experience with machine learning infrastructure workloads as well as associated networking technologies like NCCL.

• Low level systems experience, for example linux kernel tuning and eBPF

• Quickly understanding systems design tradeoffs, keeping track of rapidly evolving software systems

• Published work in performance optimization and scaling distributed systems

The annual compensation range for this role is $320,000-$405,000 USD.

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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.

About the Role

Anthropic's Infrastructure organization is foundational to our mission of developing AI systems that are reliable, interpretable, and steerable. The systems we build determine how quickly we can train new models, how reliably we can run safety experiments, and how effectively we can scale Claude to millions of users , demonstrating that safe, reliable infrastructure and frontier capabilities can go hand in hand. The Systems engineering team owns compute uptime and resilience at massive scale, building the clusters, automation, and observability that make frontier AI research possible and safely deployable to customers.

Responsibilities

• Lead infrastructure projects from design through delivery, owning scope, execution, and outcomes
• Build and maintain systems that support AI clusters at massive scale (thousands to hundreds of thousands of machines)
• Partner with cloud providers and internal teams to solve compute, networking, and reliability challenges
• Tackle difficult technical problems in your domain and proactively fill gaps in tooling, documentation, and processes
• Contribute to operational practices including incident response, postmortems, and on-call rotations

Benefits

• Competitive compensation and benefits
• Optional equity donation matching
• Generous vacation and parental leave
• Flexible working hours
• Lovely office space in which to collaborate with colleagues

Requirements

• 6+ years of software engineering experience
• Have led technical projects end-to-end over multiple months, including scoping, breaking down work, and driving delivery
• Have deep knowledge of distributed systems, reliability, and cloud platforms (Kubernetes, IaC, AWS/GCP)
• Are strong in at least one systems language (Python, Rust, Go, Java)
• Solve hard problems independently and know when to pull others in
• Help teammates grow through knowledge sharing and thoughtful technical guidance
• Communicate clearly in design docs, presentations, and cross-functional discussions

Preferred Qualifications

• Security and privacy best practice expertise
• Experience with machine learning infrastructure like GPUs, TPUs, or Trainium, as well as supporting networking infrastructure like NCCL
• Low level systems experience, for example linux kernel tuning and eBPF

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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.

At Anthropic, we are building some of the most complex and large-scale AI infrastructure in the world. As that infrastructure scales rapidly, so does the imperative to optimise how we use it. As a Software Engineer for Compute Efficiency on the Capacity team, you will play a central role in making our systems more performant, cost-effective, and sustainable—without compromising reliability or latency.

You will work across the full infrastructure stack, from cloud platforms and networking to application-level performance, and will bridge the gap between high-level research needs and low-level hardware constraints to build the most efficient AI infrastructure in the world. You will help with building the telemetry, cost attribution, and optimisation frameworks that ensure every dollar of our infrastructure investment delivers maximum value. This is a high-impact, cross-functional role at the intersection of systems engineering, financial optimisation, and AI infrastructure.

Responsibilities

• Build and evolve telemetry and monitoring systems to provide deep visibility into infrastructure performance, utilisation, and costs across our cloud and datacentre fleets.

• Design and implement cost attribution frameworks for our multi-tenant infrastructure, enabling teams to understand and optimise their resource consumption.

• Identify and resolve performance bottlenecks and capacity hotspots through deep analysis of distributed systems at scale.

• Partner closely with cloud service providers and internal stakeholders to optimise cluster configurations, workload placement, and resource utilisation across AI training and inference workloads—including large-scale clusters spanning thousands to hundreds of thousands of machines.

• Develop and champion engineering practices around efficiency, driving a culture of performance awareness and cost-conscious design across Anthropic.

• Collaborate with research and product teams to deeply understand their infrastructure needs, and design solutions that balance performance with cost efficiency.

• Drive architectural improvements and code-level optimisations across multiple services and platforms to deliver measurable utilisation and performance gains.

You may be a good fit if you:

• Have 6+ years of relevant industry experience, 1+ year leading large scale, complex projects or teams as a software engineer or tech lead

• Deep expertise in distributed systems at scale, with a strong focus on infrastructure reliability, scalability, and continuous improvement.

• Strong proficiency in at least one programming language (e.g., Python, Rust, Go, Java)

• Hands-on experience with cloud infrastructure, including Kubernetes, Infrastructure as Code, and major cloud providers such as AWS or GCP.

• Experience optimising end-to-end performance of distributed systems, including workload right-sizing and resource utilisation tuning.

• You possess a deep curiosity for how things work under the hood and have a proven ability to work independently to solve opaque performance issues

• Experience designing or working with performance and utilisation monitoring tools in large-scale, distributed environments.

• Strong problem-solving skills with the ability to work independently and navigate ambiguity.

• Excellent communication and collaboration skills—you will work closely with internal and external stakeholders to build consensus and drive projects forward.

Strong candidates may have:

• Experience with machine learning infrastructure workloads as well as associated networking technologies like NCCL.

• Low level systems experience, for example linux kernel tuning and eBPF

• Quickly understanding systems design tradeoffs, keeping track of rapidly evolving software systems

• Published work in performance optimisation and scaling distributed systems

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. 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

XML job scraping automation by YubHub

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.

About the Role

Anthropic's Infrastructure organisation is foundational to our mission of developing AI systems that are reliable, interpretable, and steerable. The systems we build determine how quickly we can train new models, how reliably we can run safety experiments, and how effectively we can scale Claude to millions of users — demonstrating that safe, reliable infrastructure and frontier capabilities can go hand in hand.

The Systems engineering team owns compute uptime and resilience at massive scale, building the clusters, automation, and observability that make frontier AI research possible and safely deployable to customers.

_Team Matching: Team matching is determined after the interview process based on interview performance, interests, and business priorities. Please note we may also consider you for different Infrastructure teams._

Responsibilities

• Own the technical strategy and roadmap for your area, translating team-level goals into concrete execution plans
• Drive cross-team initiatives to build and scale AI clusters (thousands to hundreds of thousands of machines)
• Define infrastructure architecture, ensuring the hardest problems get solved — whether by you directly or by working through others
• Partner with cloud providers and internal stakeholders to shape long-term compute, data, and infrastructure strategy
• Establish and evolve operational excellence practices (incident response, postmortem culture, on-call)

You may be a good fit if you:

• Have 10+ years of software engineering experience
• Have led complex, multi-quarter technical initiatives that span multiple teams or systems
• Can set technical direction for a team, not just execute within it
• Have deep expertise in distributed systems, reliability, and cloud platforms (Kubernetes, IaC, AWS/GCP)
• Are strong in at least one systems language (Python, Rust, Go, Java)
• Naturally uplevel the engineers around you and can redirect efforts when things are heading off track
• Build alignment across senior stakeholders and communicate effectively at all levels

Strong candidates may have:

• Security and privacy best practice expertise
• Experience with machine learning infrastructure like GPUs, TPUs, or Trainium, as well as supporting networking infrastructure like NCCL
• Low level systems experience, for example linux kernel tuning and eBPF
• Technical expertise: Quickly understanding systems design tradeoffs, keeping track of rapidly evolving software systems

_Deadline to apply: None. Applications will be reviewed on a rolling basis._

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. 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.

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.

The easiest way to understand our research directions is to read our recent research. This re

XML job scraping automation by YubHub

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.

About the Role

Anthropic's Infrastructure organisation is foundational to our mission of developing AI systems that are reliable, interpretable, and steerable. The systems we build determine how quickly we can train new models, how reliably we can run safety experiments, and how effectively we can scale Claude to millions of users — demonstrating that safe, reliable infrastructure and frontier capabilities can go hand in hand.

The Systems engineering team owns compute uptime and resilience at massive scale, building the clusters, automation, and observability that make frontier AI research possible and safely deployable to customers.

_Team Matching: Team matching is determined after the interview process based on interview performance, interests, and business priorities. Please note we may also consider you for different Infrastructure teams._

Responsibilities

• Lead infrastructure projects from design through delivery, owning scope, execution, and outcomes
• Build and maintain systems that support AI clusters at massive scale (thousands to hundreds of thousands of machines)
• Partner with cloud providers and internal teams to solve compute, networking, and reliability challenges
• Tackle difficult technical problems in your domain and proactively fill gaps in tooling, documentation, and processes
• Contribute to operational practices including incident response, postmortems, and on-call rotations

You may be a good fit if you:

• Have 6+ years of software engineering experience
• Have led technical projects end-to-end over multiple months, including scoping, breaking down work, and driving delivery
• Have deep knowledge of distributed systems, reliability, and cloud platforms (Kubernetes, IaC, AWS/GCP)
• Are strong in at least one systems language (Python, Rust, Go, Java)
• Solve hard problems independently and know when to pull others in
• Help teammates grow through knowledge sharing and thoughtful technical guidance
• Communicate clearly in design docs, presentations, and cross-functional discussions

Strong candidates may have:

• Security and privacy best practice expertise
• Experience with machine learning infrastructure like GPUs, TPUs, or Trainium, as well as supporting networking infrastructure like NCCL
• Low level systems experience, for example linux kernel tuning and eBPF
• Technical expertise: Quickly understanding systems design tradeoffs, keeping track of rapidly evolving software systems

_Deadline to apply: None. Applications will be reviewed on a rolling basis._

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. 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.

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.

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

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