Network Engineer

Anthropic•Seattle, WA

2d•Hybrid

About The Position

Anthropic is an AI safety company working to build reliable, interpretable, and steerable AI systems. Our first product, Claude, is an AI assistant built on our research into training honest, harmless AI systems. We're rapidly scaling our infrastructure to support state-of-the-art AI research and deployment. We're looking for experienced network engineers who are also skilled software developers to help build and scale the networking infrastructure that powers Claude and our AI research. This is a hands-on role where you'll work on everything from physical network builds to software-defined networking, from extending connectivity to new data center sites to building robust monitoring and automation systems. The bytes must flow! You'll be joining a small, growing team working on mission-critical infrastructure for one of the most exciting AI systems in the world. This role requires both technical depth in networking and the flexibility to solve problems across the stack—from configuring routers to writing automation, from troubleshooting physical connectivity to designing scalable network architectures.

Requirements

5+ years of experience in network engineering, with hands-on experience building and operating production networks
Strong software development skills (Python, Go, or similar) and experience building network automation, tooling, or infrastructure software
Deep understanding of networking fundamentals: TCP/IP, BGP, ISIS, OSPF, VLANs, VPCs, routing, switching, and network security
Experience with the full stack of networking—from physical layer concerns (cabling, optics, hardware) through software-defined networking
Comfort working with Linux, command-line tools, and infrastructure-as-code approaches
Track record of debugging complex distributed systems issues that span network, compute, and application layers
Strong communication skills and ability to work collaboratively with diverse teams

Nice To Haves

Experience scaling networks in cloud environments (AWS, GCP, Azure) and/or on-premises data centers
Background in DevOps/SRE practices including monitoring, observability, and reliability engineering
Experience with Kubernetes networking, container orchestration, or service mesh technologies
Prior work at startups, small ISPs, or environments requiring broad technical responsibilities
Familiarity with AI/ML infrastructure and the unique networking requirements of large-scale training clusters
Generalist mindset: You've done more than just networking—maybe you've built web applications, worked with embedded systems, or worn multiple hats in smaller organizations
End-to-end problem solver: You don't just file tickets; you chase down issues across organizational boundaries and get to root causes
Builder mentality: You're comfortable working in environments where you sometimes need to invent the solution because best practices don't exist yet
High adaptability: You thrive in evolving environments with unique challenges and can collaborate effectively with strong, opinionated technical personalities
Pragmatic technologist: You balance technical excellence with practical constraints, knowing when to build custom solutions versus leveraging existing tools

Responsibilities

Build and operate production networks: Design, deploy, and maintain high-performance networks across multiple data center sites, including managing physical infrastructure, routing protocols, and network security
Develop network automation and tooling: Write software to automate network provisioning, configuration management, and operational workflows
Ensure reliability and performance: Implement comprehensive monitoring, build debugging tools, investigate outages, and drive continuous reliability improvements
Scale networking infrastructure: Plan and execute network expansions to new sites and facilities, including working with vendors, managing physical builds, and migrating live traffic
Collaborate cross-functionally: Partner with compute, storage, and ML infrastructure teams to optimize network performance for AI workloads and troubleshoot complex distributed systems issues
Incident response: Participate in on-call rotation and lead response to network-related incidents