Software Engineer

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.

• 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, leading 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, unified query interfaces, and AI-assisted diagnostic tooling.
• Improve fleet-wide efficiency by turning continuous profiling and utilization telemetry into actionable optimization insights across CPU, memory, and accelerator fleets.
• Partner with Research, Inference, Product, and Infrastructure teams to ensure observability solutions meet the unique needs of each organization.

• Experience building and operating large-scale observability or monitoring infrastructure.
• Hands-on experience with observability signals end to end, from instrumentation through ingest to query and analysis.
• Understanding of high-throughput telemetry pipelines and the tradeoffs involved in collecting, storing, and querying operational data at scale.
• Comfort debugging below the application layer, in the kernel, the network stack, or the hardware.
• Excellent communication skills and the ability to partner with internal teams to improve their operational visibility and incident response capabilities.
• Ability to work independently on ambiguous, high-impact technical challenges.
• Preferred: Experience building or operating eBPF-based observability in production.
• Preferred: Experience running continuous profiling at fleet scale.
• Preferred: Kernel- and syscall-level debugging experience and performance engineering skills.
• Preferred: Experience profiling or instrumenting accelerator workloads.
• Preferred: Experience operating metrics systems at very high cardinality, or large-scale telemetry storage backends.
• Preferred: Experience with log storage migrations or operating columnar databases (e.g., ClickHouse, BigQuery) for analytics workloads.
• Preferred: Experience with OpenTelemetry instrumentation, collector pipelines, and tail-based sampling strategies.
• Preferred: Interest in applying AI/LLMs to operational workflows.

• Annual Salary: $320,000 - $485,000 USD.
• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience.
• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time.
• Visa sponsorship: We do sponsor visas!