Staff Software Engineer, Observability & Profiling

<div class="content-intro"><h2><strong>About Anthropic</strong></h2> <p>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.</p></div><h2>About the role</h2> <p>Anthropic is seeking Software Engineers to join our Observability team within the Infrastructure organization. The Observability team owns the monitoring and telemetry infrastructure that every engineer and researcher at Anthropic depends on—from metrics and logging pipelines to distributed tracing, profiling, error analytics, alerting, and the dashboards and query interfaces that make it all actionable. By joining this team, you'll have a direct impact on the reliability and operational excellence of Anthropic's research and product systems.</p> <p>As Anthropic scales its infrastructure across massive GPU, TPU, and Trainium clusters, the volume and complexity of operational data is growing by orders of magnitude—and an increasing share of the hardest problems live below the application layer. We're building next-generation observability systems—high-throughput telemetry pipelines, fleet-wide continuous profiling, eBPF-based tracing and network visibility, and agentic diagnostic tools—so engineers can detect, diagnose, and resolve issues in minutes rather than hours, even when the answer lies in the kernel, the network stack, or an accelerator rather than on a dashboard.</p> <h2>Key responsibilities</h2> <ul> <li>Design and build scalable telemetry ingest and storage pipelines for metrics, logs, traces, and error data across Anthropic's multi-cluster infrastructure</li> <li>Build observability solutions that give engineers deep, low-overhead visibility into system behavior across the fleet</li> <li>Own and evolve core observability platforms, d