About the Role

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.

Responsibilities

• Develop appropriate Service Level Objectives for large language model serving and training systems, balancing availability/latency with development velocity.


• Design and implement monitoring systems including availability, latency and other salient metrics.


• Assist in the design and implementation of high-availability language model serving infrastructure capable of handling the needs of millions of external customers and high-traffic internal workloads.


• Develop and manage automated failover and recovery systems for model serving deployments across multiple regions and cloud providers.


• Lead incident response for critical AI services, ensuring rapid recovery and systematic improvements from each incident


• Build and maintain cost optimization systems for large-scale AI infrastructure, focusing on accelerator (GPU/TPU/Trainium) utilization and efficiency

Requirements

• Have extensive experience with distributed systems observability and monitoring at scale


• Understand the unique challenges of operating AI infrastructure, including model serving, batch inference, and training pipelines


• Have proven experience implementing and maintaining SLO/SLA frameworks for business-critical services


• Are comfortable working with both traditional metrics (latency, availability) and AI-specific metrics (model performance, training convergence)


• Have experience with chaos engineering and systematic resilience testing


• Can effectively bridge the gap between ML engineers and infrastructure teams


• Have excellent communication skills.

Education Requirements

We require at least a Bachelor's degree in a related field or equivalent experience.