Technical Program Manager, Infrastructure

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

Anthropic's Infrastructure organization is the engine that powers our mission. 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 frontier models, production infrastructure serving millions of users reliably, and developer platforms that help engineers move fast without breaking things.

As a Technical Program Manager for Infrastructure, you’ll work across multiple infrastructure domains to coordinate complex programs that have broad organizational impact. You’ll be solving novel scaling challenges at the frontier of what's possible, all while maintaining the security and reliability our mission demands. This role is ideal for someone who thrives in ambiguity and believes their job is to make everyone around them more effective.

You’ll partner closely with engineering leadership to drive strategic initiatives while ensuring seamless coordination between research, engineering, and product teams

What you’ll do

Developer Productivity & Tooling Drive cross-functional programs to improve developer environments, CI/CD infrastructure, and release processes that enable rapid innovation while maintaining high security standards Coordinate large-scale migrations and platform modernization efforts across engineering teams Partner with teams to measure and improve developer productivity metrics, identifying bottlenecks and driving systematic improvements Lead initiatives to integrate AI tools into development workflows, helping Anthropic be at the forefront of AI-assisted research and engineering Infrastructure Reliability & Operations Drive programs to establish and achieve reliability targets across training infrastructure and production services Coordinate incident response improvements, post-mortem processes, and on-call rotations that help teams operate effectively Establish metrics and dashboards to track infrastructure health, capacity utilization, and operational excellence Cross-functional Coordination Serve as the critical bridge between infrastructure teams, research, and product, translating technical complexities into clear updates for a variety of audiences Consult with stakeholders to deeply understand infrastructure, data, and compute needs, identifying solutions to support frontier research and product development Drive alignment on priorities and timelines across teams with competing constraints You May Be a Good Fit If You Have 5+ years of technical program management experience, with a track record of successfully delivering complex infrastructure programs in ML/AI systems or large-scale distributed systems Have deep technical understanding of infrastructure systems—enough to engage substantively with engineers, identify technical risks, and add value beyond project tracking Excel at creating structure and processes in ambiguous environments, bringing clarity to complex cross-team initiatives Have strong stakeholder management skills and can build trust with both technical and non-technical partners Are comfortable navigating competing priorities and using data to drive technical decisions Have experience with developer productivity initiatives, CI/CD systems, or infrastructure scaling Thrive in fast-paced environments and can balance strategic planning with tactical execution Are obsessed with reliability, scalability, security, and continuous improvement Have a passion for supporting internal partners like research to understand their unique needs Are passionate about AI infrastructure and understand the unique challenges of building and operating systems at frontier scale Experience with Kubernetes, cloud platforms (AWS, GCP, Azure), and ML infrastructure (GPU/TPU/Trainium clusters) Background working with research teams and translating their needs into concrete technical requirements Experience driving adoption of AI tools to improve engineering productivity Familiarity with observability tooling and practices Deadline to Apply: None, applications will be received on a rolling basis.