Senior Software Engineer, AI Reliability Engineering

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.