Senior Staff+ Software Engineer, Node Infra at Anthropic

Hybrid - San Francisco, CA; New York City, NY; Seattle, WA

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Anthropic’s Infrastructure organization is foundational to our mission of developing AI systems that are reliable, interpretable, and steerable. The role focuses on owning the technical strategy and roadmap for node lifecycle management, driving cross‑team initiatives to build and scale AI clusters across multiple clouds, and designing systems that automatically detect and remediate unhealthy hardware. Candidates will lead complex, multi‑quarter technical initiatives, collaborate with cloud providers and internal teams, and mentor junior engineers while ensuring operational excellence and high‑throughput, latency‑sensitive production reliability.

Salary

USD 405,000 - 485,000

Requirements

Skills

  • Deep expertise in distributed systems, reliability, and cloud platforms (Kubernetes, IaC, AWS, GCP, Azure)
  • Strong proficiency in at least one systems language (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 spanning multiple teams or systems
  • Ability to build alignment across senior stakeholders and communicate effectively at all levels
  • 12+ years of software engineering experience, including time as a technical lead
  • Experience managing large‑scale compute infrastructure at hyperscale (10K+ nodes)
  • Depth in Kubernetes internals, cluster orchestration systems, or node provisioning pipelines
  • Low‑level systems experience (kernel, virtualization, device drivers, firmware, 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)
  • Skill in quickly understanding systems design tradeoffs

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 systems that detect, isolate, and remediate unhealthy hardware automatically
  • Define infrastructure architecture, ensuring the hardest problems get solved
  • 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 through technical mentorship and coaching

Technologies

KubernetesInfrastructure as Code (IaC)AWSGCPAzureTerraformRustGoPythonGPUsTPUsTrainiumMesosBorgKarpenterEFARDMAInfiniBandCluster orchestrationDevice driversKernelVirtualizationFirmware

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