Staff Software Engineer, Node Infra

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., * 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

Do you have experience in Virtualization?, Do you have a Bachelor's degree?, * 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, * 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, 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.

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

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., 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.