The opportunity
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…
What you'll do
Design and build scalable telemetry ingest and storage pipelines for metrics,: logs, traces, and error data across Anthropic's multi-cluster infrastructure
Build observability solutions that give engineers deep, low-overhead: visibility into system behavior across the fleet
Own and evolve core observability platforms, driving migrations and: architectural improvements that improve reliability, reduce cost, and scale with organizational growth
Build instrumentation libraries, SDKs, and eBPF-based auto-instrumentation to: emit high-quality telemetry, with and without code changes
Reduce mean time to detection and resolution by building cross-signal: correlation—from kernel-level events up to application traces—unified query interfaces, and AI-assisted diagnostic tooling
Drive fleet-wide efficiency by turning continuous profiling and utilization: telemetry into actionable optimization insights across CPU, memory, and accelerator fleets
What they're looking for
- + years of relevant industry experience, including building and operating: large-scale observability or monitoring infrastructure
- Experience building or operating eBPF-based observability in: production—tracing, profiling, or network visibility
- Experience running continuous profiling at fleet scale, including managing overhead budgets and symbolization
- Kernel- and syscall-level debugging experience and performance engineering craft
- Experience profiling or instrumenting accelerator workloads
- Experience operating metrics systems at very high cardinality, or large-scale telemetry storage backends
- Experience with OpenTelemetry instrumentation, collector pipelines, and tail-based sampling strategies
- Interest in applying AI/LLMs to operational workflows such as automated root: cause analysis, anomaly detection, or intelligent alerting
