Staff Software Engineer, Node Infra

Anthropic · London, UK · Software Engineering - Infrastructure · listed May 7, 2026

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The shape of it

Seniority

Staff

Experience asked

7+ years

Where

Hybrid

Requirements listed

Length

1,064 words

In the posting’s own words

Node Infra owns the full lifecycle of accelerator capacity at Anthropic. We ingest and provision compute from all major cloud providers and from datacenters custom-built for Anthropic, stand up and scale the clusters behind one of the industry's largest AI compute fleets, 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.

What it asks for · 5

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

Also a plus

7+ 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

What the job covers

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

Tools and skills named

Cloud & infra

Kubernetes3×
AWS
Azure
Distributed systems
GCP
Linux
Terraform

Models & research

GPU2×
Machine learning2×
Inference

Frameworks

Node.js4×

Languages

Go
Python
Rust

Ways of working

Mentorship2×
On-call

Product & design

Roadmap

Words the posting leans on

systems11×
infrastructure5×
node5×
build4×
cloud4×
compute4×
experience4×
scale4×
technical4×
accelerator3×
capacity3×
clusters3×
fleet3×
kubernetes3×
cloud providers2×
design2×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

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