Anthropic
Staff Infrastructure Engineer, Cluster Infrastructure
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.
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.
Cluster Infra owns the full lifecycle of compute clusters at Anthropic. We build agent-driven automation for cluster provisioning and lifecycle management across all major cloud providers and our own datacenters. Our systems stand up clusters that are interconnected with high bandwidth, secure-by-default, and able to automatically drain and recover in response to failure. As a Staff engineer on this team, you'll set the technical direction for how Anthropic brings compute online - at a moment when the scale of that compute is growing faster than at almost any company in the world.
Key responsibilities
- Own the technical strategy and roadmap for agent-driven cluster lifecycle management - provisioning, updates and decommissioning
- Partner across teams to ensure new compute capacity is ingested on time
- Align with partner teams on physical build-out and leverage cloud solutions to deliver high-bandwidth inter-cluster connectivity
- Collaborate with security owners to ensure clusters are provisioned secure-by-default
- Define and drive strategy on cluster scalability, homogeneity and fault tolerance
- Work closely with cloud providers and internal research, inference and product teams to shape long-term compute, data, and infrastructure strategy
- Establish and evolve operational-excellence practices: incident response, postmortem culture and on-call health
- Support the growth of engineers around you through technical mentorship and coaching
Minimum qualifications
- Deep expertise in distributed systems, reliability, and cloud platforms (e.g., Kubernetes, IaC, AWS/GCP/Azure)
- Strong proficiency in at least one systems language (e.g., Rust, Go, or Python), IaC proficiency with Terraform.
- Track record of leading complex, multi-quarter technical initiatives spanning multiple teams or systems
- Ability to build alignment across senior stakeholders and communicate effectively at all levels
Preferred qualifications
- 8+ years of software engineering experience, including time as a technical lead setting direction for a team
- Experience operating large-scale compute infrastructure at hyperscale (100+ clusters, 10K+ nodes)
- Depth in one or more of: Kubernetes internals, cluster provisioning and management systems, cluster orchestration systems (Mesos, Borg-like)
- Experience with cloud networking: VPC design and peering, Shared VPC/Transit Gateway, Cloud Interconnect/Direct Connect, Cloud NAT, cross-cloud private connectivity, BGP and route control, edge load balancing and DDoS mitigation (Cloud Armor / AWS Shield)
- Experience with cluster and host networking: CNI (Cilium), eBPF, NetworkPolicy, multi-NIC, sFlow, service mesh (Istio/Envoy/Linkerd, mTLS)
- Experience with cluster security: pod security standards and admission control, RBAC and least-privilege IAM, node and container hardening, supply-chain/image provenance
- Deep experience with infrastructure-as-code (Terraform, Atlantis), workflow orchestration (Temporal, Argo Workflows)
- Skill in quickly understanding systems design tradeoffs and keeping track of rapidly evolving software systems
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.
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.
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, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process
Ready to apply?
Apply to Anthropic
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.
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.
Node Infra owns the full lifecycle of accelerator capacity at Anthropic. We ingest and provision compute from all major CSPs and our own datacenters, stand up and scale clusters from thousands to hundreds of thousands of hosts, and build the health, diagnostics and repair automation that keep every GPU, TPU and Trainium node in the fleet usable and ready to power Anthropic’s frontier AI research.
Key responsibilities
- Own the technical strategy and roadmap for node lifecycle management - ingestion, bring-up, health checking, and automated repair
- Drive cross-team initiatives to build and scale AI clusters across multiple clouds and accelerator families
- Design and operate the systems that detect, isolate, and remediate unhealthy hardware automatically, driving up fleet MTBI and minimizing stranded capacity
- Define infrastructure architecture, ensuring the hardest problems get solved - whether by you directly or by working through others
- Work closely with cloud providers and internal research/inference/product teams to shape long-term compute, data, and infrastructure strategy
- Establish and evolve operational excellence practices (incident response, postmortem culture, on-call)
- Support the growth of engineers around you through technical mentorship and coaching
Minimum qualifications
- Deep expertise in distributed systems, reliability, and cloud platforms (e.g., Kubernetes, IaC, AWS/GCP/Azure)
- Strong proficiency in at least one systems language (e.g., Rust, Go, or Python), IaC proficiency with Terraform.
- Hands-on experience with machine learning accelerators (GPUs, TPUs, or Trainium)
- Track record of leading complex, multi-quarter technical initiatives that span multiple teams or systems
- Ability to build alignment across senior stakeholders and communicate effectively at all levels
Preferred qualifications
- 8+ years of software engineering experience, including time as a technical lead setting direction for a team
- Experience managing large scale compute infrastructure at hyperscale (10K+ nodes), including capacity management and efficiency
- Depth in one or more of: Kubernetes internals (scheduler, autoscaler, kubelet, Karpenter), cluster orchestration systems (Mesos, Borg-like), or node provisioning pipelines
- Low-level systems experience: kernel, virtualization, device drivers, firmware, or hardware health/diagnostics daemons
- Familiarity with high-performance networking (EFA, RDMA, InfiniBand) for distributed ML workloads.
- Demonstrated ownership of production reliability for high-throughput, latency-sensitive systems
- Contributions to relevant open-source projects (Kubernetes, Linux kernel, container runtimes, etc.)
- Skill in quickly understanding systems design tradeoffs and keeping track of rapidly evolving software systems
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.
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.
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, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process
Ready to apply?
Apply to Anthropic
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.
About the role
Anthropic runs some of the largest Kubernetes clusters in the industry. We have fleets of hundreds of thousands of nodes across multiple cloud providers and datacenters to train, research, and serve frontier AI models. The Kubernetes Platform team owns the Kubernetes control plane that makes those clusters work.
We are operating at a scale where the defaults stop working. We own the scheduler and extend it to place topology-sensitive ML workloads across thousands of accelerators at once. We scale the control plane itself — apiserver, etcd, controllers — so it stays responsive as object counts and node counts grow by orders of magnitude. And we build the core cluster services every workload depends on, like service discovery, so they hold up under the same pressure.
We make sure the control plane is fast, correct, and always available. Your work will directly determine whether Anthropic can keep reliably and safely training frontier models as our compute footprint continues to grow.
Key responsibilities
- Own, operate, and extend the Kubernetes scheduler for Anthropic's accelerator fleets, including custom scheduling plugins and policies for gang scheduling, topology awareness, and preemption
- Scale the Kubernetes control plane (apiserver, etcd, controller-manager) to support clusters far beyond typical limits, and find the next bottleneck before it finds us
- Design, build, and operate core cluster services such as service discovery that every workload in the fleet depends on
- Build and maintain custom controllers, operators, and CRDs
- Partner with research, training, and inference to understand workload shapes and turn their requirements into platform capabilities
- Collaborate with cloud providers on required features and escalations
- Participate in on-call, lead incident response, and design processes (postmortems, runbooks, SLOs) that help the team avoid repeating failures
Minimum qualifications
- Significant software engineering experience building and operating production distributed systems
- Proficiency in at least one systems-appropriate language (e.g., Go, Python, Rust, or C++)
- Deep, hands-on Kubernetes experience (well beyond "user of”) into scheduler, controllers, apiserver, or operating large multi-tenant clusters
- Demonstrated ability to debug complex issues across the stack, from API behavior down to node and network-level root causes
- A track record of designing for reliability, correctness, and clear failure semantics in systems other engineers depend on
- Strong written and verbal communication; comfort building consensus with internal stakeholders
Preferred qualifications
- Experience with Kubernetes internals or contributions: kube-scheduler / scheduling framework, apiserver, etcd, client-go, controller-runtime, or similar
- Experience building or operating cluster schedulers or batch systems (e.g., Kueue, Volcano, Slurm, or in-house equivalents)
- Background scaling control planes or coordination systems (etcd, ZooKeeper, Consul, or large DNS/service-mesh deployments)
- Familiarity with ML infrastructure: GPUs, TPUs, or Trainium; gang scheduling; topology-aware placement; collective networking such as NCCL
- Experience with GCP and/or AWS, including GKE/EKS internals and Infrastructure as Code
- Low-level systems experience such as Linux kernel tuning, cgroups, or eBPF
- 8+ years of relevant industry experience, including time leading large, ambiguous infrastructure projects
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.
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.
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, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process
Ready to apply?
Apply to Anthropic
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.
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.
Cluster Infra owns the full lifecycle of compute clusters at Anthropic. We build agent-driven automation for cluster provisioning and lifecycle management across all major cloud providers and our own datacenters. Our systems stand up clusters that are interconnected with high bandwidth, secure-by-default, and able to automatically drain and recover in response to failure. As a Staff engineer on this team, you'll set the technical direction for how Anthropic brings compute online - at a moment when the scale of that compute is growing faster than at almost any company in the world.
Key responsibilities
- Own the technical strategy and roadmap for agent-driven cluster lifecycle management - provisioning, updates and decommissioning
- Partner across teams to ensure new compute capacity is ingested on time
- Align with partner teams on physical build-out and leverage cloud solutions to deliver high-bandwidth inter-cluster connectivity
- Collaborate with security owners to ensure clusters are provisioned secure-by-default
- Define and drive strategy on cluster scalability, homogeneity and fault tolerance
- Work closely with cloud providers and internal research, inference and product teams to shape long-term compute, data, and infrastructure strategy
- Establish and evolve operational-excellence practices: incident response, postmortem culture and on-call health
- Support the growth of engineers around you through technical mentorship and coaching
Minimum qualifications
- Deep expertise in distributed systems, reliability, and cloud platforms (e.g., Kubernetes, IaC, AWS/GCP/Azure)
- Strong proficiency in at least one systems language (e.g., Rust, Go, or Python), IaC proficiency with Terraform.
- Track record of leading complex, multi-quarter technical initiatives spanning multiple teams or systems
- Ability to build alignment across senior stakeholders and communicate effectively at all levels
Preferred qualifications
- 8+ years of software engineering experience, including time as a technical lead setting direction for a team
- Experience operating large-scale compute infrastructure at hyperscale (100+ clusters, 10K+ nodes)
- Depth in one or more of: Kubernetes internals, cluster provisioning and management systems, cluster orchestration systems (Mesos, Borg-like)
- Experience with cloud networking: VPC design and peering, Shared VPC/Transit Gateway, Cloud Interconnect/Direct Connect, Cloud NAT, cross-cloud private connectivity, BGP and route control, edge load balancing and DDoS mitigation (Cloud Armor / AWS Shield)
- Experience with cluster and host networking: CNI (Cilium), eBPF, NetworkPolicy, multi-NIC, sFlow, service mesh (Istio/Envoy/Linkerd, mTLS)
- Experience with cluster security: pod security standards and admission control, RBAC and least-privilege IAM, node and container hardening, supply-chain/image provenance
- Deep experience with infrastructure-as-code (Terraform, Atlantis), workflow orchestration (Temporal, Argo Workflows)
- Skill in quickly understanding systems design tradeoffs and keeping track of rapidly evolving software systems
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.
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.
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, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process
Ready to apply?
Apply to Anthropic
Staff Software Engineer, Kubernetes Platform
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.
About the role
Anthropic runs some of the largest Kubernetes clusters in the industry. We have fleets of hundreds of thousands of nodes across multiple cloud providers and datacenters to train, research, and serve frontier AI models. The Kubernetes Platform team owns the Kubernetes control plane that makes those clusters work.
We are operating at a scale where the defaults stop working. We own the scheduler and extend it to place topology-sensitive ML workloads across thousands of accelerators at once. We scale the control plane itself — apiserver, etcd, controllers — so it stays responsive as object counts and node counts grow by orders of magnitude. And we build the core cluster services every workload depends on, like service discovery, so they hold up under the same pressure.
We make sure the control plane is fast, correct, and always available. Your work will directly determine whether Anthropic can keep reliably and safely training frontier models as our compute footprint continues to grow.
Key responsibilities
- Own, operate, and extend the Kubernetes scheduler for Anthropic's accelerator fleets, including custom scheduling plugins and policies for gang scheduling, topology awareness, and preemption
- Scale the Kubernetes control plane (apiserver, etcd, controller-manager) to support clusters far beyond typical limits, and find the next bottleneck before it finds us
- Design, build, and operate core cluster services such as service discovery that every workload in the fleet depends on
- Build and maintain custom controllers, operators, and CRDs
- Partner with research, training, and inference to understand workload shapes and turn their requirements into platform capabilities
- Collaborate with cloud providers on required features and escalations
- Participate in on-call, lead incident response, and design processes (postmortems, runbooks, SLOs) that help the team avoid repeating failures
Minimum qualifications
- Significant software engineering experience building and operating production distributed systems
- Proficiency in at least one systems-appropriate language (e.g., Go, Python, Rust, or C++)
- Deep, hands-on Kubernetes experience (well beyond "user of”) into scheduler, controllers, apiserver, or operating large multi-tenant clusters
- Demonstrated ability to debug complex issues across the stack, from API behavior down to node and network-level root causes
- A track record of designing for reliability, correctness, and clear failure semantics in systems other engineers depend on
- Strong written and verbal communication; comfort building consensus with internal stakeholders
Preferred qualifications
- Experience with Kubernetes internals or contributions: kube-scheduler / scheduling framework, apiserver, etcd, client-go, controller-runtime, or similar
- Experience building or operating cluster schedulers or batch systems (e.g., Kueue, Volcano, Slurm, or in-house equivalents)
- Background scaling control planes or coordination systems (etcd, ZooKeeper, Consul, or large DNS/service-mesh deployments)
- Familiarity with ML infrastructure: GPUs, TPUs, or Trainium; gang scheduling; topology-aware placement; collective networking such as NCCL
- Experience with GCP and/or AWS, including GKE/EKS internals and Infrastructure as Code
- Low-level systems experience such as Linux kernel tuning, cgroups, or eBPF
- 8+ years of relevant industry experience, including time leading large, ambiguous infrastructure projects
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.
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.
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, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process
Ready to apply?
Apply to Anthropic
Staff+ Software Engineer, Developer Productivity
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.
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.
Developer Productivity owns the end-to-end experience of how engineers and researchers at Anthropic develop, build, test, and ship code at scale — from the source control and language ecosystems that underpin our monorepo, to the build and CI infrastructure that keeps thousands of daily builds running reliably across multiple cloud providers, to the developer acceleration tooling that deeply integrates Claude into engineering workflows.
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
- Define infrastructure architecture, ensuring the hardest problems get solved — whether by you directly or by working through others
- Design and build scalable, reliable distributed infrastructure and shared libraries that support high-volume workloads across all engineering teams
- Own and evolve build environments, package management, and dependency systems to enable fast, reproducible builds
- Define and implement language ecosystem standards, tooling, and frameworks that drive developer productivity across research and production workloads
You may be a good fit if you:
- Have deep experience with build systems, CI/CD pipelines, and/or developer tooling in a large monorepo environment
- Have strong proficiency in Python, Rust and/or Go
- Are obsessed with developer productivity and reducing friction in the software development lifecycle
- Have experience with container orchestration and infrastructure at scale
- Have excellent communication skills and enjoy supporting internal partners to improve their development experience
- Are excited about designing foundational systems and are comfortable working independently on ambiguous, high-impact technical challenges
Strong candidates may have:
- 15+ years (not including internships or co-ops) of experience in a Software Engineer role, building and operating large-scale developer infrastructure
- 3+ years (not including internships or co-ops) of experience leading large scale complex projects or teams as a tech lead
- Experience with CI orchestration tools (Buildkite, Jenkins, GitHub Actions, or similar) and merge queue management at scale
- Experience building or operating remote build execution systems (Bazel Remote Execution API, BuildBarn, BuildBuddy, or similar)
- Experience with Nix/NixOS/Docker and managing large image / package sets at scale
- Experience building CLI tools, developer-facing services, and GitHub API and automation workflows
Deadline to apply: None. Applications will be reviewed on a rolling basis.
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.
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.
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, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process
Ready to apply?
Apply to Anthropic
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.
About the role:
Our Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry's largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators.
The team has a dual mandate: maximizing compute efficiency to serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms.
Strong candidates may also have experience with:
- High-performance, large-scale distributed systems
- Implementing and deploying machine learning systems at scale
- Load balancing, request routing, or traffic management systems
- LLM inference optimization, batching, and caching strategies
- Kubernetes and cloud infrastructure (AWS, GCP)
- Python or Rust
You may be a good fit if you:
- Have significant software engineering experience, particularly with distributed systems
- Are results-oriented, with a bias towards flexibility and impact
- Pick up slack, even if it goes outside your job description
- Want to learn more about machine learning systems and infrastructure
- Thrive in environments where technical excellence directly drives both business results and research breakthroughs
- Care about the societal impacts of your work
Representative projects across the org:
- Designing intelligent routing algorithms that optimize request distribution across thousands of accelerators
- Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads
- Building production-grade deployment pipelines for releasing new models to millions of users
- Integrating new AI accelerator platforms to maintain our hardware-agnostic competitive advantage
- Contributing to new inference features (e.g., structured sampling, prompt caching)
- Supporting inference for new model architectures
- Analyzing observability data to tune performance based on real-world production workloads
- Managing multi-region deployments and geographic routing for global customers
Deadline to apply: None. Applications will be reviewed on a rolling basis.
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.
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.
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, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process
Ready to apply?
Apply to Anthropic
Staff + Sr. Software Engineer, Inference Deployment
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.
About the Role
Our mandate is to make inference deployment boring and unattended.
Anthropic serves Claude to millions of users across GPUs, TPUs, and Trainium — and every model update must reach production safely, quickly, and without disrupting service. We're building the systems that make inference deployment continuous and unattended.
As a Software Engineer on the Launch Engineering team, you'll design and build the deployment infrastructure that moves inference code from merge to production. This is a resource-constrained optimization problem at its core: validation and deployment consume the same accelerator chips that serve customer traffic — your deploys compete with live user requests for the same hardware. Every model brings different fleet sizes, startup times, and correctness requirements, so the system must adapt continuously. You'll build systems that navigate these constraints — orchestrating validation, scheduling deployments intelligently, and driving down cycle time from merge to production.
If you've built deployment systems at scale and gravitate toward the hardest problems at the intersection of automation and resource management, this team will give you an outsized scope to work on them.
Responsibilities
- Own deployment orchestration that continuously moves validated inference builds into production across GPU, TPU, and Trainium fleets, unattended under normal conditions
- Improve capacity-aware deployment scheduling to maximize deployment throughput against constrained accelerator budgets and variable fleet sizes
- Extend deployment observability — dashboards and tooling that answer "what code is running in production," "where is my commit," and "what validation passed for this deploy"
- Drive down cycle time from code merge to production with pipeline architectures that minimize serial dependencies and maximize parallelism
- Optimize fleet rollout strategies for large-scale deployments across thousands of GPU, TPU, and Trainium chips, minimizing disruption to serving capacity
- Evolve self-service model onboarding so that new models can be added to the continuous deployment pipeline without Launch Engineering involvement
- Partner across the Inference organization with teams owning validation, autoscaling, and model routing to integrate deployment automation with their systems
You May Be a Good Fit If You Have
- 5+ years of experience building deployment, release, or delivery infrastructure at scale
- Strong software engineering skills with experience designing systems that manage complex state machines and multi-stage pipelines
- Experience with deployment systems where resource constraints shape the design — whether that's fleet capacity, network bandwidth, hardware availability, or coordinated rollout windows
- A track record of building automation that measurably improves deployment velocity and reliability
- Proficiency with Kubernetes-based deployments, rolling update mechanics, and container orchestration
- Comfort working across the stack — from backend services and databases to CLI tools and web UIs
- Strong communication skills and the ability to work closely with oncall engineers, model teams, and infrastructure partners
Strong Candidates May Also Have
- Experience with ML inference or training infrastructure deployment, particularly across multiple accelerator types (GPU, TPU, Trainium)
- Background in capacity planning or resource-constrained scheduling (e.g., bin-packing, fleet management, job scheduling with hardware affinity)
- Experience with progressive delivery in systems with long validation cycles: canary/soak testing, blue-green deployments, traffic shifting, automated rollback
- Experience at companies with large-scale release engineering challenges (mobile release trains, monorepo deployments, multi-datacenter rollouts)
- Experience with Python and/or Rust in production systems
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.
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.
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, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process
Ready to apply?
Apply to Anthropic
Staff + Sr. Software Engineer, Inference
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.
About the role
Our Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry's largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators.
The team has a dual mandate: maximizing compute efficiency to serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms.You may be a good fit if you:
- Have significant software engineering experience, particularly with distributed systems
- Are results-oriented, with a bias towards flexibility and impact
- Pick up slack, even if it goes outside your job description
- Enjoy pair programming (we love to pair!)
- Want to learn more about machine learning systems and infrastructure
- Thrive in environments where technical excellence directly drives both business results and research breakthroughs
- Care about the societal impacts of your work
Strong candidates may also have experience with:
- High-performance, large-scale distributed systems
- Implementing and deploying machine learning systems at scale
- Load balancing, request routing, or traffic management systems
- LLM inference optimization, batching, and caching strategies
- Kubernetes and cloud infrastructure (AWS, GCP, Azure)
- Python or Rust
Representative projects:
- Designing intelligent routing algorithms that optimize request distribution across thousands of accelerators
- Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads
- Building production-grade deployment pipelines for releasing new models to millions of users
- Integrating new AI accelerator platforms to maintain our hardware-agnostic competitive advantage
- Contributing to new inference features (e.g., structured sampling, prompt caching)
- Supporting inference for new model architectures
- Analyzing observability data to tune performance based on real-world production workloads
- Managing multi-region deployments and geographic routing for global customers
Deadline to apply: None. Applications will be reviewed on a rolling basis.
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.
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.
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, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process
Ready to apply?
Apply to Anthropic
Staff + Sr. Software Engineer, Cloud Inference
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.
About the Role
The Cloud Inference team scales and optimizes Claude to serve the massive audiences of developers and enterprise companies across AWS, GCP, Azure, and future cloud service providers (CSPs). We own the end-to-end product of Claude on each cloud platform—from API integration and intelligent request routing to inference execution, capacity management, and day-to-day operations.
Our engineers are extremely high leverage: we simultaneously drive multiple major revenue streams while optimizing one of Anthropic's most precious resources—compute. As we expand to more cloud platforms, the complexity of managing inference efficiently across providers with different hardware, networking stacks, and operational models grows significantly. We need engineers who can navigate these platform differences, build robust abstractions that work across providers, and make smart infrastructure decisions that keep us cost-effective at massive scale.
Your work will increase the scale at which our services operate, accelerate our ability to reliably launch new frontier models and innovative features to customers across all platforms, and ensure our LLMs meet rigorous safety, performance, and security standards.
What You'll Do
- Design and build infrastructure that serves Claude across multiple CSPs, accounting for differences in compute hardware, networking, APIs, and operational models
- Collaborate with CSP partner engineering teams to resolve operational issues, influence provider roadmaps, and stand up end-to-end serving on new cloud platforms
- Design and evolve CI/CD automation systems, including validation and deployment pipelines, that reliably ship new model versions to millions of users across cloud platforms without regressions
- Design interfaces and tooling abstractions across CSPs that enable cost-effective inference management, scale across providers, and reduce per-platform complexity
- Contribute to capacity planning and autoscaling strategies that dynamically match supply with demand across CSP validation and production workloads
- Optimize inference cost and performance across providers—designing workload placement and routing systems that direct requests to the most cost-effective accelerator and region
- Contribute to inference features that must work consistently across all platforms
- Analyze observability data across providers to identify performance bottlenecks, cost anomalies, and regressions, and drive remediation based on real-world production workloads
You May Be a Good Fit If You:
- Have significant software engineering experience, with a strong background in high-performance, large-scale distributed systems serving millions of users
- Have experience building or operating services on at least one major cloud platform (AWS, GCP, or Azure), with exposure to Kubernetes, Infrastructure as Code or container orchestration
- Have strong interest in inference
- Thrive in cross-functional collaboration with both internal teams and external partners
- Are a fast learner who can quickly ramp up on new technologies, hardware platforms, and provider ecosystems
- Are highly autonomous and self-driven, taking ownership of problems end-to-end with a bias toward flexibility and high-impact work
- Pick up slack, even when it goes outside your job description
Strong Candidates May Also Have Experience With
- Direct experience working with CSP partner teams to scale infrastructure or products across multiple platforms, navigating differences in networking, security, privacy, billing, and managed service offerings
- A background in building platform-agnostic tooling or abstraction layers that work across cloud providers
- Hands-on experience with capacity management, cost optimization, or resource planning at scale across heterogeneous environments
- Strong familiarity with LLM inference optimization, batching, caching, and serving strategies
- Experience with Machine learning infrastructure including GPUs, TPUs, Trainium, or other AI accelerators
- Background designing and building CI/CD systems that automate deployment and validation across cloud environments
- Solid understanding of multi-region deployments, geographic routing, and global traffic management
- Proficiency in Python or Rust
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.
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.
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, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process
Ready to apply?
Apply to Anthropic
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.
About the role:
Our Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry's largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators.
The team has a dual mandate: maximizing compute efficiency to serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms.
Strong candidates may also have experience with:
- High-performance, large-scale distributed systems
- Implementing and deploying machine learning systems at scale
- Load balancing, request routing, or traffic management systems
- LLM inference optimization, batching, and caching strategies
- Kubernetes and cloud infrastructure (AWS, GCP)
- Python or Rust
You may be a good fit if you:
- Have significant software engineering experience, particularly with distributed systems
- Are results-oriented, with a bias towards flexibility and impact
- Pick up slack, even if it goes outside your job description
- Want to learn more about machine learning systems and infrastructure
- Thrive in environments where technical excellence directly drives both business results and research breakthroughs
- Care about the societal impacts of your work
Representative projects across the org:
- Designing intelligent routing algorithms that optimize request distribution across thousands of accelerators
- Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads
- Building production-grade deployment pipelines for releasing new models to millions of users
- Integrating new AI accelerator platforms to maintain our hardware-agnostic competitive advantage
- Contributing to new inference features (e.g., structured sampling, prompt caching)
- Supporting inference for new model architectures
- Analyzing observability data to tune performance based on real-world production workloads
- Managing multi-region deployments and geographic routing for global customers
Deadline to apply: None. Applications will be reviewed on a rolling basis.
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.
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.
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, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process
Ready to apply?
Apply to Anthropic
Staff + Sr. Software Engineer, AI Reliability
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.
About the Role
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.
Reliability here is an emergent phenomenon that transcends any single team's boundaries, so someone has to zoom out and look at the whole picture. That's us -- and it means few teams at Anthropic offer this kind of dynamic, cross-cutting exposure to the systems that matter most.
Responsibilities:
- Develop appropriate Service Level Objectives for large language model serving systems, balancing availability and latency with development velocity
- Design and implement monitoring and observability systems across the token path
- Assist in the design and implementation of high-availability serving infrastructure across multiple regions and cloud provider
- Lead incident response for critical AI services, ensuring rapid recovery, thorough incident reviews, and systematic improvements
- Support the reliability of safeguard model serving -- critical for both site reliability and Anthropic's safety commitments.
You may be a good fit if you:
- Have strong distributed systems, infrastructure, or reliability backgrounds -- we're looking for reliability-minded software engineers and SREs
- Are curious and brave -- comfortable jumping into unfamiliar systems during an incident and helping drive resolution even when you don't have deep expertise yet
- Think holistically about how systems compose and where the seams are
- Can build lasting relationships across teams -- our engagement model depends on being welcomed as teammates, not outsiders with opinions
- Care about users and feel ownership over outcomes, even for systems you don't own
- Have excellent communication and collaboration skills -- you'll be partnering across the entire company
- Bring diverse experience -- the team's strength comes from people who've built product stacks, scaled databases, run massive distributed systems, and everything in between.
Strong candidates may also:
- Have been an SRE, Production Engineer, or in similar reliability-focused roles on large scale systems
- Have experience operating large-scale model serving or training infrastructure (>1000 GPUs)
- Have experience with one or more ML hardware accelerators (GPUs, TPUs, Trainium)
- Understand ML-specific networking optimizations like RDMA and InfiniBand
- Have expertise in AI-specific observability tools and frameworks
- Have experience with chaos engineering and systematic resilience testing
- Have contributed to open-source infrastructure or ML 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.
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.
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, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process
Ready to apply?
Apply to Anthropic
Staff Software Engineer, Node Infra
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.
Staff Infrastructure Engineer, Node Infra
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.
Node Infra owns the full lifecycle of accelerator capacity at Anthropic. We ingest and provision compute from all major CSPs and our own datacenters, stand up and scale clusters from thousands to hundreds of thousands of hosts, and build the health, diagnostics and repair automation that keep every GPU, TPU and Trainium node in the fleet usable and ready to power Anthropic’s frontier AI research.
Key responsibilities
- Own the technical strategy and roadmap for node lifecycle management - ingestion, bring-up, health checking, and automated repair
- Drive cross-team initiatives to build and scale AI clusters across multiple clouds and accelerator families
- Design and operate the systems that detect, isolate, and remediate unhealthy hardware automatically, driving up fleet MTBI and minimizing stranded capacity
- Define infrastructure architecture, ensuring the hardest problems get solved - whether by you directly or by working through others
- Work closely with cloud providers and internal research/inference/product teams to shape long-term compute, data, and infrastructure strategy
- Establish and evolve operational excellence practices (incident response, postmortem culture, on-call)
- Support the growth of engineers around you through technical mentorship and coaching
Minimum qualifications
- Deep expertise in distributed systems, reliability, and cloud platforms (e.g., Kubernetes, IaC, AWS/GCP/Azure)
- Strong proficiency in at least one systems language (e.g., Rust, Go, or Python), IaC proficiency with Terraform.
- Hands-on experience with machine learning accelerators (GPUs, TPUs, or Trainium)
- Track record of leading complex, multi-quarter technical initiatives that span multiple teams or systems
- Ability to build alignment across senior stakeholders and communicate effectively at all levels
Preferred qualifications
- 8+ years of software engineering experience, including time as a technical lead setting direction for a team
- Experience managing large scale compute infrastructure at hyperscale (10K+ nodes), including capacity management and efficiency
- Depth in one or more of: Kubernetes internals (scheduler, autoscaler, kubelet, Karpenter), cluster orchestration systems (Mesos, Borg-like), or node provisioning pipelines
- Low-level systems experience: kernel, virtualization, device drivers, firmware, or hardware health/diagnostics daemons
- Familiarity with high-performance networking (EFA, RDMA, InfiniBand) for distributed ML workloads.
- Demonstrated ownership of production reliability for high-throughput, latency-sensitive systems
- Contributions to relevant open-source projects (Kubernetes, Linux kernel, container runtimes, etc.)
- Skill in quickly understanding systems design tradeoffs and keeping track of rapidly evolving software systems
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.
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.
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, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process
Ready to apply?
Apply to Anthropic
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.
About the role
Anthropic is expanding beyond cloud infrastructure, and this role sits at the heart of that effort. As a Staff Engineer on the Datacenter Server Lifecycle team, you will own the end-to-end operational journey of every machine in our facility — from initial provisioning and deployment, across its working life, through maintenance and refresh, and all the way to decommissioning. This is greenfield work: you will help define the processes, tooling, and operational standards that govern how we run and retire hardware at scale.
A distinguishing aspect of this role is its deep intersection with security. The machines in our datacenter handle some of the most sensitive workloads in AI — training frontier models and serving millions of users interacting with Claude. Ensuring that every machine in the fleet is trusted, attested, and operating with a verified chain of integrity from the hardware up is a core part of the job, not an afterthought. You will partner closely with our Infrastructure Security team to define and enforce trusted compute standards across the lifecycle, from secure provisioning through end-of-life handling.
Key responsibilities
- Lead the build-out of automation to support datacenters containing tens of thousands of servers.
- Define and own the end-to-end server lifecycle strategy — from provisioning and deployment through operation, maintenance, refresh, and decommissioning — and maintain automation and operational procedures for common lifecycle events (e.g., hardware failures, firmware upgrades, fleet rotations).
- Partner closely with Infrastructure Security to design and enforce trusted compute standards across the server lifecycle.
- Work closely with our Networking team to ensure end-to-end connectivity across all sites.
- Build and maintain tooling to track machine health, configuration, and operational status across the full datacenter fleet.
Minimum qualifications
- Hands-on experience with server hardware, including rack deployment, cabling, troubleshooting, and understanding failure modes at scale.
- End-to-end understanding of hardware lifecycle management: asset tracking, provisioning workflows, maintenance scheduling, and decommissioning practices.
- Proficiency in at least one programming language (e.g., Python, Rust, Go, or Java).
- Working knowledge of modern cloud infrastructure, including Kubernetes, Infrastructure as Code, AWS, and GCP.
- Ability to communicate clearly and build consensus with a wide range of stakeholders.
- Comfort navigating ambiguity and making progress on complex, cross-functional problems.
- Willingness to travel occasionally to datacenter sites across North America.
Preferred qualifications
- 8+ years of experience in datacenter operations, hardware infrastructure management, or a closely related discipline.
- Hands-on experience with GPU or AI accelerator hardware (e.g., NVIDIA A100/H100, AMD MI300, Google TPUs, or AWS Trainium) and an understanding of their operational demands.
- Familiarity with modern provisioning tooling such as coreboot, LinuxBoot, or u-root.
- Experience building or contributing to datacenter automation or fleet management platforms.
- Experience building and deploying server operating system distributions across thousands of hosts.
- Background in large-scale capacity planning and hardware refresh strategy, ideally at a hyperscaler or large cloud provider.
- Experience with trusted compute and hardware security concepts such as secure boot, TPM, hardware attestation, and firmware verification — or a strong desire to develop deep expertise in this area.
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.
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.
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, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process
Ready to apply?
Apply to Anthropic
Staff Engineer, Datacenter Server Lifecycle
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.
About the role
Anthropic is expanding beyond cloud infrastructure, and this role sits at the heart of that effort. As a Staff Engineer on the Datacenter Server Lifecycle team, you will own the end-to-end operational journey of every machine in our facility — from initial provisioning and deployment, across its working life, through maintenance and refresh, and all the way to decommissioning. This is greenfield work: you will help define the processes, tooling, and operational standards that govern how we run and retire hardware at scale.
A distinguishing aspect of this role is its deep intersection with security. The machines in our datacenter handle some of the most sensitive workloads in AI — training frontier models and serving millions of users interacting with Claude. Ensuring that every machine in the fleet is trusted, attested, and operating with a verified chain of integrity from the hardware up is a core part of the job, not an afterthought. You will partner closely with our Infrastructure Security team to define and enforce trusted compute standards across the lifecycle, from secure provisioning through end-of-life handling.
Key responsibilities
- Lead the build-out of automation to support datacenters containing tens of thousands of servers.
- Define and own the end-to-end server lifecycle strategy — from provisioning and deployment through operation, maintenance, refresh, and decommissioning — and maintain automation and operational procedures for common lifecycle events (e.g., hardware failures, firmware upgrades, fleet rotations).
- Partner closely with Infrastructure Security to design and enforce trusted compute standards across the server lifecycle.
- Work closely with our Networking team to ensure end-to-end connectivity across all sites.
- Build and maintain tooling to track machine health, configuration, and operational status across the full datacenter fleet.
Minimum qualifications
- Hands-on experience with server hardware, including rack deployment, cabling, troubleshooting, and understanding failure modes at scale.
- End-to-end understanding of hardware lifecycle management: asset tracking, provisioning workflows, maintenance scheduling, and decommissioning practices.
- Proficiency in at least one programming language (e.g., Python, Rust, Go, or Java).
- Working knowledge of modern cloud infrastructure, including Kubernetes, Infrastructure as Code, AWS, and GCP.
- Ability to communicate clearly and build consensus with a wide range of stakeholders.
- Comfort navigating ambiguity and making progress on complex, cross-functional problems.
- Willingness to travel occasionally to datacenter sites across North America.
Preferred qualifications
- 8+ years of experience in datacenter operations, hardware infrastructure management, or a closely related discipline.
- Hands-on experience with GPU or AI accelerator hardware (e.g., NVIDIA A100/H100, AMD MI300, Google TPUs, or AWS Trainium) and an understanding of their operational demands.
- Familiarity with modern provisioning tooling such as coreboot, LinuxBoot, or u-root.
- Experience building or contributing to datacenter automation or fleet management platforms.
- Experience building and deploying server operating system distributions across thousands of hosts.
- Background in large-scale capacity planning and hardware refresh strategy, ideally at a hyperscaler or large cloud provider.
- Experience with trusted compute and hardware security concepts such as secure boot, TPM, hardware attestation, and firmware verification — or a strong desire to develop deep expertise in this area.
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.
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.
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, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process
Ready to apply?
Apply to Anthropic
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.
About the role
Anthropic is seeking talented and experienced Software Engineers to join our Continuous Integration (CI) team within the Developer Productivity organization. The CI team is responsible for the infrastructure that enables hundreds of engineers to ship code safely and efficiently to production. By joining this team, you'll have a direct impact on the velocity and reliability of Anthropic's research and product development.
The CI team manages Anthropic's continuous integration system, which includes:
- CI infrastructure for automated testing and code quality assurance across our monorepo, designed to scale with rapid growth
- Test infrastructure that runs on Kubernetes clusters across multiple cloud providers, handling intelligent test selection, execution, and reporting for a large and complex test suite
- Merge queue management and complex branching strategies that ensure code quality at scale
- CI tooling and automation to improve developer productivity and reduce operational overhead
Responsibilities
- Design and build highly reliable, scalable CI infrastructure that supports thousands of daily builds across multiple cloud providers
- Develop intelligent test selection systems that reduce CI time while maintaining code quality
- Build and improve incident response automation, including cluster load shedding, automatic recovery, and observability tooling
- Improve test infrastructure reliability through flake detection, quarantine systems, and test state management
You may be a good fit if you
- Have 10+ years of relevant industry experience building and operating large-scale CI/CD systems
- Have deep experience with CI orchestration tools (Buildkite, Jenkins, GitHub Actions, or similar)
- Are obsessed with developer productivity and reducing friction in the software development lifecycle
- Have experience with container orchestration at scale
- Have excellent communication skills and enjoy supporting internal partners
- Care deeply about reliability and building systems that "never fail the same way twice"
Strong candidates may also have
- Experience with merge queues and branch management at scale
- Experience with test infrastructure, including intelligent test selection and flake management
- Experience building CLI tools and developer-facing services
- GitHub API and automation experience
Deadline to apply: None. Applications will be reviewed on a rolling basis.
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.
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.
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, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process
Ready to apply?
Apply to Anthropic
Senior / Staff+ Software Engineer, Voice Platform
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.
About the role
We're building the infrastructure that lets people talk to Claude—real-time, bidirectional voice conversations that feel natural, responsive, and safe. This is foundational work for how millions of people will interact with AI.
The Voice Platform team designs and operates the serving systems, streaming pipelines, and APIs that bring Anthropic's audio models from research into production across Claude.ai, our mobile apps, and the Anthropic API. You'll work at the intersection of real-time media, low-latency inference, and distributed systems—building infrastructure where every millisecond of latency is felt by the user.
We partner closely with the Audio research team, who train the speech understanding and generation models, and with product teams shipping voice experiences to users. Your job is to make those models fast, reliable, and delightful to talk to at scale.
What you'll do
- Design and build the real-time streaming infrastructure that powers voice conversations with Claude—ingesting microphone audio, orchestrating model inference, and streaming synthesized speech back with minimal latency
- Build low-latency serving systems for speech models, optimizing time-to-first-audio and end-to-end conversational responsiveness
- Develop the public and internal APIs that expose voice capabilities to Claude.ai, mobile clients, and third-party developers
- Own the audio transport layer—codecs, jitter buffers, adaptive bitrate, packet loss recovery—so conversations stay smooth across unreliable networks
- Build observability and quality-measurement systems for voice: latency distributions, audio quality metrics, interruption handling, and turn-taking accuracy
- Partner with Audio research to move new model architectures from experiment to production, and feed real-world performance data back into research
- Collaborate with mobile and product engineering on client-side audio capture, playback, and the end-to-end user experience
You may be a good fit if you
- Have 6+ years of experience building distributed systems, real-time infrastructure, or platform services at scale
- Have shipped production systems where latency is measured in tens of milliseconds and users notice when you miss
- Are comfortable working across the stack—from transport protocols and serving infrastructure up to the APIs product teams build on
- Are results-oriented, with a bias toward flexibility and impact
- Pick up slack, even if it goes outside your job description
- Enjoy pair programming (we love to pair!)
- Care about the societal impacts of voice AI and want to help shape how these systems are developed responsibly
- Are comfortable with ambiguity—voice is a fast-moving space, and you'll help define the architecture as we learn what works
Strong candidates may also have experience with
- Real-time media protocols and stacks: WebRTC, RTP, gRPC bidirectional streaming, or WebSockets at scale
- Audio engineering fundamentals: codecs (Opus, AAC), voice activity detection, echo cancellation, jitter buffering, or audio DSP
- Low-latency ML inference serving, streaming model outputs, or GPU-based serving infrastructure
- Telephony, live streaming, video conferencing, or voice assistant platforms
- Mobile audio pipelines on iOS (AVAudioEngine, AudioUnits) or Android (Oboe, AAudio)
- Working alongside ML researchers to productionize models—speech experience is a plus but not required
Representative projects
- Driving time-to-first-audio below human perceptual thresholds by co-designing the serving pipeline with the Audio research team
- Building a streaming inference orchestrator that interleaves speech recognition, LLM reasoning, and speech synthesis with overlapping execution
- Designing the voice mode API surface for the Anthropic API so developers can build their own voice agents on Claude
- Implementing graceful barge-in and interruption handling so users can cut Claude off mid-sentence naturally
- Instrumenting end-to-end audio quality metrics and building dashboards that catch regressions before users do
Deadline to apply: None. Applications will be reviewed on a rolling basis.
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.
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.
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, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process
Ready to apply?
Apply to Anthropic
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.
About the role
Our Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry's largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators. The team has a dual mandate: maximizing compute efficiency to serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms.
As a Staff Software Engineer on our Inference team, you will work end to end, identifying and addressing key infrastructure blockers to serve Claude to millions of users while enabling breakthrough AI research. Strong candidates should have familiarity with performance optimization, distributed systems, large-scale service orchestration, and intelligent request routing. Familiarity with LLM inference optimization, batching strategies, and multi-accelerator deployments is highly encouraged but not strictly necessary.
Strong candidates may also have experience with
- High-performance, large-scale distributed systems
- Implementing and deploying machine learning systems at scale
- Load balancing, request routing, or traffic management systems
- LLM inference optimization, batching, and caching strategies
- Kubernetes and cloud infrastructure (AWS, GCP)
- Python or Rust
You may be a good fit if you
- Have significant software engineering experience, particularly with distributed systems
- Are results-oriented, with a bias towards flexibility and impact
- Pick up slack, even if it goes outside your job description
- Want to learn more about machine learning systems and infrastructure
- Thrive in environments where technical excellence directly drives both business results and research breakthroughs
- Care about the societal impacts of your work
Representative projects across the org
- Designing intelligent routing algorithms that optimize request distribution across thousands of accelerators
- Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads
- Building production-grade deployment pipelines for releasing new models to millions of users
- Integrating new AI accelerator platforms to maintain our hardware-agnostic competitive advantage
- Contributing to new inference features (e.g., structured sampling, prompt caching)
- Supporting inference for new model architectures
- Analyzing observability data to tune performance based on real-world production workloads
- Managing multi-region deployments and geographic routing for global customers
Deadline to apply: None. Applications will be reviewed on a rolling basis.
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.
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.
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, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process
Ready to apply?
Apply to Anthropic
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.
About the role
We are seeking an experienced Engineering Manager to lead the Cloud Inference team for AWS. You will lead your team to scale and optimize Claude to serve the massive audiences of developers and enterprise companies using AWS. You will own the end-to-end product of Claude on AWS, including API, load balancing, inference, capacity and operations. Your team will ensure our LLMs meet rigorous performance, safety and security standards and enhance our core infrastructure for packaging, testing, and deploying inference technology across the globe. Your work will increase the scale at which Anthropic operates and accelerate our ability to reliably launch new frontier models and innovative features to customers across all platforms.
Responsibilities:
- Set technical strategy and oversee development of Claude on AWS across all layers of the technical stack.
- Collaborate across teams and companies to deeply understand product, infrastructure, operations and capacity needs, identifying potential solutions to support frontier LLM serving
- Work closely with cross-functional stakeholders across companies to align on goals and drive outcomes
- Create clarity for the team and stakeholders in an ambiguous and evolving environment
- Take an inclusive approach to hiring and coaching top technical talent, and support a high performing team
- Design and run processes (e.g. postmortem review, incident response, on-call rotations) that help the team operate effectively and never fail the same way twice
You may be a good fit if you:
- Have 10+ years of experience in high-scale, high-reliability software development, particularly infrastructure or capacity management
- Have 5+ years of engineering management experience
- Experience recruiting, scaling, and retaining engineering talent in a high growth environment
- Have experience scaling products, resources and operations to accommodate rapid growth
- Are deeply interested in the potential transformative effects of advanced AI systems and are committed to ensuring their safe development
- Excel at building strong relationships and strategy with stakeholders across engineering, product, finance, and sales
- Have experience working with external partners to align goals and deliver impact
- Enjoy working in a fast-paced, early environment; comfortable with adapting priorities as driven by the rapidly evolving AI space
- Have excellent written and verbal communication skills
- Demonstrated success building a culture of belonging and engineering excellence
- Are motivated by developing AI responsibly and safely
- Are willing and able to travel frequently between Seattle and the SF Bay Area
Strong candidates may also have experience with:
- Experience with machine learning infrastructure like GPUs, TPUs, or Trainium, as well as supporting networking infrastructure like NCCL
- Experience as a Product Manager
- Experience with deployment and capacity management automation
- Security and privacy best practice expertise
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.
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.
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, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process
Ready to apply?
Apply to Anthropic
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.
About the Role
Claude has your back. AIRE has Claude's. Help us keep Claude reliable for everyone who depends on it.
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.
Reliability here is an emergent phenomenon that transcends any single team's boundaries, so someone has to zoom out and look at the whole picture. That's us -- and it means few teams at Anthropic offer this kind of dynamic, cross-cutting exposure to the systems that matter most.
Responsibilities
- Develop appropriate Service Level Objectives for large language model serving systems, balancing availability and latency with development velocity.
- Design and implement monitoring and observability systems across the token path.
- Assist in the design and implementation of high-availability serving infrastructure across multiple regions and cloud providers
- Lead incident response for critical AI services, ensuring rapid recovery, thorough incident reviews, and systematic improvements.
- Support the reliability of safeguard model serving -- critical for both site reliability and Anthropic's safety commitments.
You may be a good fit if you
- Have strong distributed systems, infrastructure, or reliability backgrounds -- we're looking for reliability-minded software engineers and SREs.
- Are curious and brave -- comfortable jumping into unfamiliar systems during an incident and helping drive resolution even when you don't have deep expertise yet.
- Think holistically about how systems compose and where the seams are.
- Can build lasting relationships across teams -- our engagement model depends on being welcomed as teammates, not outsiders with opinions.
- Care about users and feel ownership over outcomes, even for systems you don't own.
- Have excellent communication and collaboration skills -- you'll be partnering across the entire company.
- Bring diverse experience -- the team's strength comes from people who've built product stacks, scaled databases, run massive distributed systems, and everything in between.
Strong candidates may also
- Have been an SRE, Production Engineer, or in similar reliability-focused roles on large scale systems
- Have experience operating large-scale model serving or training infrastructure (>1000 GPUs).
- Have experience with one or more ML hardware accelerators (GPUs, TPUs, Trainium).
- Understand ML-specific networking optimizations like RDMA and InfiniBand.
- Have expertise in AI-specific observability tools and frameworks.
- Have experience with chaos engineering and systematic resilience testing.
- Have contributed to open-source infrastructure or ML 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.
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.
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, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process
Ready to apply?
Apply to Anthropic
Infrastructure Engineer, Sandboxing
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.
About the role
Anthropic is seeking an experienced Infrastructure Engineer to join our Sandboxing team within the Research organization. In this role, you'll build and scale the systems that enable researchers to safely execute and experiment with AI-generated code and interactions in isolated environments.
As our models become more capable, the infrastructure supporting secure execution environments becomes increasingly critical. You'll work on distributed systems that must operate reliably at significant scale while maintaining strong security boundaries. Your work will directly support Anthropic's mission to develop AI systems that are safe, beneficial, and trustworthy.
Responsibilities
- Design, build, and operate distributed backend systems that power secure sandboxed execution environments
- Scale infrastructure to meet growing research and product demands while maintaining reliability and performance
- Implement and maintain serverless architectures and container orchestration systems
- Collaborate with research teams to understand requirements and translate them into robust infrastructure solutions
- Develop monitoring, alerting, and observability systems to ensure operational excellence
- Participate in on-call rotations and incident response to maintain system reliability
- Contribute to infrastructure automation and tooling that improves developer productivity
- Partner with security teams to ensure sandboxing infrastructure maintains appropriate isolation guarantees
You may be a good fit if you
- Have 5+ years of experience building and operating backend infrastructure at scale
- Have deep expertise in distributed systems design and implementation
- Have strong operational experience, including debugging complex production issues
- Are proficient with cloud platforms, particularly GCP/GCS (experience with AWS or Azure is also valuable)
- Have experience with containerization technologies (Docker, Kubernetes) and understand their security implications
- Are comfortable working with infrastructure as code and modern DevOps practices
- Have strong programming skills in languages such as Python, Go, or Rust
- Are results-oriented with a bias towards flexibility and impact
- Care about the societal impacts of your work and are motivated by Anthropic's mission
Strong candidates may also have experience with
- Serverless architectures and functions-as-a-service platforms (Cloud Functions, Cloud Run, Lambda)
- Designing and implementing secure multi-tenant systems
- High-performance computing environments or ML infrastructure
- Linux systems internals, including namespaces, cgroups, and seccomp
- Network security and isolation techniques
- Building systems that support research workflows and rapid iteration
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.
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.
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, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process
Ready to apply?
Apply to Anthropic
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.
About the Role
Claude has your back. AIRE has Claude's. Help us keep Claude reliable for everyone who depends on it.
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.
Reliability here is an emergent phenomenon that transcends any single team's boundaries, so someone has to zoom out and look at the whole picture. That's us -- and it means few teams at Anthropic offer this kind of dynamic, cross-cutting exposure to the systems that matter most.
Responsibilities
- Develop appropriate Service Level Objectives for large language model serving systems, balancing availability and latency with development velocity.
- Design and implement monitoring and observability systems across the token path.
- Assist in the design and implementation of high-availability serving infrastructure across multiple regions and cloud providers
- Lead incident response for critical AI services, ensuring rapid recovery, thorough incident reviews, and systematic improvements.
- Support the reliability of safeguard model serving -- critical for both site reliability and Anthropic's safety commitments.
You may be a good fit if you
- Have strong distributed systems, infrastructure, or reliability backgrounds -- we're looking for reliability-minded software engineers and SREs.
- Are curious and brave -- comfortable jumping into unfamiliar systems during an incident and helping drive resolution even when you don't have deep expertise yet.
- Think holistically about how systems compose and where the seams are.
- Can build lasting relationships across teams -- our engagement model depends on being welcomed as teammates, not outsiders with opinions.
- Care about users and feel ownership over outcomes, even for systems you don't own.
- Have excellent communication and collaboration skills -- you'll be partnering across the entire company.
- Bring diverse experience -- the team's strength comes from people who've built product stacks, scaled databases, run massive distributed systems, and everything in between.
Strong candidates may also
- Have been an SRE, Production Engineer, or in similar reliability-focused roles on large scale systems
- Have experience operating large-scale model serving or training infrastructure (>1000 GPUs).
- Have experience with one or more ML hardware accelerators (GPUs, TPUs, Trainium).
- Understand ML-specific networking optimizations like RDMA and InfiniBand.
- Have expertise in AI-specific observability tools and frameworks.
- Have experience with chaos engineering and systematic resilience testing.
- Have contributed to open-source infrastructure or ML 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.
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.
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, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process
Ready to apply?
Apply to Anthropic
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.
About the role:
Our Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry's largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators.
The team has a dual mandate: maximizing compute efficiency to serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms.
As a Staff Software Engineer on our Inference team, you will work end to end, identifying and addressing key infrastructure blockers to serve Claude to millions of users while enabling breakthrough AI research. Strong candidates should have familiarity with performance optimization, distributed systems, large-scale service orchestration, and intelligent request routing. Familiarity with LLM inference optimization, batching strategies, and multi-accelerator deployments is highly encouraged but not strictly necessary.
Strong candidates may also have experience with:
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High-performance, large-scale distributed systems
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Implementing and deploying machine learning systems at scale
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Load balancing, request routing, or traffic management systems
-
LLM inference optimization, batching, and caching strategies
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Kubernetes and cloud infrastructure (AWS, GCP)
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Python or Rust
You may be a good fit if you:
-
Have significant software engineering experience, particularly with distributed systems
-
Are results-oriented, with a bias towards flexibility and impact
-
Pick up slack, even if it goes outside your job description
-
Want to learn more about machine learning systems and infrastructure
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Thrive in environments where technical excellence directly drives both business results and research breakthroughs
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Care about the societal impacts of your work
Representative projects across the org:
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Designing intelligent routing algorithms that optimize request distribution across thousands of accelerators
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Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads
-
Building production-grade deployment pipelines for releasing new models to millions of users
-
Integrating new AI accelerator platforms to maintain our hardware-agnostic competitive advantage
-
Contributing to new inference features (e.g., structured sampling, prompt caching)
-
Supporting inference for new model architectures
-
Analyzing observability data to tune performance based on real-world production workloads
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Managing multi-region deployments and geographic routing for global customers
Deadline to apply: None. Applications will be reviewed on a rolling basis.
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.
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.
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, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process
Ready to apply?
Apply to Anthropic
Staff+ Software Engineer, Databases
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.
About the role
We're looking for experienced engineers to build and scale the database infrastructure that powers both Claude's product offerings and Anthropic's research initiatives. As a Software Engineer on the Databases team, you will architect and operate database systems that both enable millions of users to interact with Claude and support cutting-edge AI research.
This is a unique opportunity to tackle database challenges at unprecedented scale. You'll develop the database strategy for Anthropic, design systems that handle billions of API requests, create storage solutions that work seamlessly across GCP, AWS, and diverse deployment models, and build the reliable data layer that accelerates research experimentation.
Responsibilities:
- Drive the technical direction for database solutions used across Product and Research
- Design and implement database solutions that scale to support millions of users across Claude's product ecosystem
- Build and scale database systems through 100x+ growth while maintaining reliability and performance
- Architect data storage solutions that work seamlessly across GCP, AWS, first-party deployments, third-party deployments, and other environments
- Develop database infrastructure that serves both product and research workloads with different performance characteristics
- Partner with product and research teams to understand data requirements and build infrastructure that accelerates innovation
- Optimize database performance, reliability, and cost efficiency at massive scale
- Make critical build vs. buy decisions for database technologies
You might be a good fit if you:
- Have 10+ years (not including internships or co-ops) of experience in a Software Engineer role, building and scaling database systems
- Have 3+ years (not including internships or co-ops) of experience leading large scale, complex projects or teams as an engineer or tech lead
- Possess deep expertise in distributed database architectures and OLTP systems at scale
- Have successfully scaled databases through massive growth at high-growth companies
- Can balance the speed of a startup environment with the reliability needs of production systems
- Excel at technical leadership and cross-functional collaboration
- Are passionate about building the data layer that enables next-generation AI capabilities
Strong candidates may also have:
- Deep expertise scaling PostgreSQL, MySQL, DynamoDB, or similar database systems
- Experience with Redis, Temporal, vector databases, or async job processing frameworks
- Experience building multi-cloud or hybrid cloud database solutions
- Knowledge of database orchestration and automation at scale
- Background at companies known for database excellence
Note: Prior AI/ML infrastructure experience is not required. We value deep infrastructure/databases expertise from any domain.
Deadline to apply: None. Applications will be reviewed on a rolling basis.
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.
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.
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, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process
Ready to apply?
Apply to Anthropic
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.
Anthropic is seeking a Linux OS and System Programming Subject Matter Expert to join our Infrastructure team. In this role, you'll work on accelerating and optimizing our virtualization and VM workloads that power our AI infrastructure. Your expertise in low-level system programming, kernel optimization, and virtualization technologies will be crucial in ensuring Anthropic can scale our compute infrastructure efficiently and reliably for training and serving frontier AI models.
Responsibilities:
- Optimize our virtualization stack, improving performance, reliability, and efficiency of our VM environments
- Design and implement kernel modules, drivers, and system-level components to enhance our compute infrastructure
- Investigate and resolve performance bottlenecks in virtualized environments
- Collaborate with cloud engineering teams to optimize interactions between our workloads and underlying hardware
- Develop tooling for monitoring and improving virtualization performance
- Work with our ML engineers to understand their computational needs and optimize our systems accordingly
- Contribute to the design and implementation of our next-generation compute infrastructure
- Share knowledge with team members on low-level systems programming and Linux kernel internals
- Partner with cloud providers to influence hardware and platform features for AI workloads
You may be a good fit if you:
- Have experience with Linux kernel development, system programming, or related low-level software engineering
- Understand virtualization technologies (KVM, Xen, QEMU, etc.) and their performance characteristics
- Have experience optimizing system performance for compute-intensive workloads
- Are familiar with modern CPU architectures and memory systems
- Have strong C/C++ programming skills and ideally experience with systems languages like Rust
- Understand Linux resource management, scheduling, and memory management
- Have experience profiling and debugging system-level performance issues
- Are comfortable diving into unfamiliar codebases and technical domains
- Are results-oriented, with a bias towards practical solutions and measurable impact
- Care about the societal impacts of AI and are passionate about building safe, reliable systems
Strong candidates may also have experience with:
- GPU virtualization and acceleration technologies
- Cloud infrastructure at scale (AWS, GCP)
- Container technologies and their underlying implementation (Docker, containerd, runc, OCI)
- eBPF programming and kernel tracing tools
- OS-level security hardening and isolation techniques
- Developing custom scheduling algorithms for specialized workloads
- Performance optimization for ML/AI specific workloads
- Network stack optimization and high-performance networking
- Experience with TPUs, custom ASICs, or other ML accelerators
Representative projects:
- Optimizing kernel parameters and VM configurations to reduce inference latency for large language models
- Implementing custom memory management schemes for large-scale distributed training
- Developing specialized I/O schedulers to prioritize ML workloads
- Creating lightweight virtualization solutions tailored for AI inference
- Building monitoring and instrumentation tools to identify system-level bottlenecks
- Enhancing communication between VMs for distributed training workloads
Deadline to apply: None. Applications will be reviewed on a rolling basis.
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.
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.
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, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process
Ready to apply?
Apply to Anthropic