As a Software Engineer for Compute Efficiency on the Capacity team, you will play a central role in making our systems more performant, cost-effective, and sustainable—without compromising reliability or latency. You will work across the full infrastructure stack, from cloud platforms and networking to application-level performance, and will bridge the gap between high-level research needs and low-level hardware constraints to build the most efficient AI infrastructure in the world.

Build and evolve telemetry and monitoring systems to provide deep visibility into infrastructure performance, utilization, and costs across our cloud and datacenter fleets.

Design and implement cost attribution frameworks for our multi-tenant infrastructure, enabling teams to understand and optimize their resource consumption.

Identify and resolve performance bottlenecks and capacity hotspots through deep analysis of distributed systems at scale.

Partner closely with cloud service providers and internal stakeholders to optimize cluster configurations, workload placement, and resource utilization across AI training and inference workloads—including large-scale clusters spanning thousands to hundreds of thousands of machines.

Develop and champion engineering practices around efficiency, driving a culture of performance awareness and cost-conscious design across Anthropic.

Collaborate with research and product teams to deeply understand their infrastructure needs, and design solutions that balance performance with cost efficiency.

Drive architectural improvements and code-level optimizations across multiple services and platforms to deliver measurable utilization and performance gains.