Engineering Manager, Systems

Anthropic•San Francisco, NY

4d•Hybrid

About The Position

Anthropic's Infrastructure organization is the engine that powers our mission to develop AI systems that are safe, beneficial, and understandable. Every breakthrough in AI safety research and every interaction users have with Claude depends on the systems we build and operate: massive clusters for training, production infrastructure serving millions of users reliably, and developer platforms that help engineers move fast without breaking things. This isn't typical infrastructure work. We're building at the frontier of what's possible, solving novel scaling challenges that few organizations face with a high degree of security, all in service of ensuring transformative AI benefits humanity. If you're energized by your technical work directly enabling some of the most important research happening today, Infrastructure at Anthropic is the best place to make a real difference. The Systems engineering team enables Anthropic to rapidly research and deploy safe frontier models at scale by owning compute uptime and resilience. We build resilience into Anthropic's infrastructure and support rapid scaling of our clusters with frontier hardware through relentless automation. This allows Anthropic's research to remain on the frontier of what's possible and makes research breakthroughs safely and reliably deployable to customers. We are seeking an experienced engineering leader to manage the part of our Systems team that looks after our Kubernetes control plane and custom schedulers. You'll lead initiatives supporting some of the largest, most sophisticated clusters in the industry used to train, research, and ultimately serve AI models. Your work will be crucial in ensuring Anthropic can continue reliably and safely training frontier models.

Requirements

Have 3+ years of experience managing technical teams of more than 6 people
Have strong leadership ability with experience managing and growing senior engineers
Have excellent communication skills to build consensus with stakeholders, both internally and externally
Possess deep knowledge of modern cloud infrastructure including Kubernetes, Infrastructure as Code, and major cloud providers (AWS, GCP)
Are passionate about infrastructure reliability, scalability, security, and continuous improvement
Have a track record of supporting internal partners and understanding their needs

Nice To Haves

Experience with Machine learning infrastructure including accelerators (GPUs, TPUs, Trainium) and supporting networking infrastructure like NCCL
Container orchestration platforms such as EKS and GKE
Working on teams that contribute to OSS Kubernetes and other CNCF tools
Infrastructure as Code tools like Terraform
Autoscaling technologies including Cluster Autoscaler and Karpenter
Low-level systems experience, for example Linux kernel tuning and eBPF
Security and privacy best practice expertise
Managing initiatives across multiple products and teams

Responsibilities

Manage a team of engineers building and operating world-class infrastructure at scale
Lead build out of industry-leading AI clusters (thousands to hundreds of thousands of machines), partnering closely with cloud service providers on cluster build out and required features
Consult with different stakeholders to deeply understand infrastructure and compute needs, identifying potential solutions to support frontier research and product development
Set technical strategy and oversee development of high-scale, reliable infrastructure systems
Hire and coach top technical talent
Design processes (e.g., postmortem review, incident response, on-call rotations) that help the team operate effectively and never fail the same way twice
Drive continuous improvement in system reliability, scalability, and security
Work closely with Research and Product Engineering teams to ensure infrastructure meets their evolving needs