Software Engineer, Networking
About Anthropic
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.
About the Role
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 Python automation, from troubleshooting physical connectivity to designing scalable network architectures.
Key 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
About You
We're looking for engineers who think of themselves as problem-solvers first, who happen to have deep networking expertise. The ideal candidate has:
Required:
- 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
Preferred:
- 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
What makes a great fit:
- 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
The expected base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.
Annual Salary:
$320,000 - $485,000 USD
Logistics
Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.
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.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
How we're different
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.
Come work with us!
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
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