Staff Infrastructure Engineer, Cluster Infrastructure

Anthropic
Charing Cross, United Kingdom
9 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Shift work
Languages
English
Experience level
Senior
Compensation
£ 325K

Job location

Charing Cross, United Kingdom

Tech stack

Amazon Web Services (AWS)
Azure
Border Gateway Protocol
Cloud Computing
DDoS Mitigation
Distributed Systems
Fault Tolerance
Identity and Access Management
Python
Node.js
Peering
Role-Based Access Control
Cloud Services
Mesos
Software Engineering
Software Systems
Workflow Management Systems
Network Switches
Load Balancing
Istio
Amazon Web Services (AWS)
Kubernetes
Linkerd (Service Mesh)
Terraform

Job description

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., * 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

Requirements

  • 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, * 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, 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.

Benefits & conditions

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

About the company

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.

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