Engineering Manager - AI Reliability

AnthropicSan Francisco, CA, United States

9 hours ago

Job type

Full-time

Job description

Overview

Engineering Manager - Serving Infrastructure at Anthropic. Lead one of our Reliability Engineering teams responsible for large language model serving, focusing on reliability metrics and using modern AI capabilities to improve reliability engineering.

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. Our team is a quickly growing group of researchers, engineers, policy experts, and business leaders building beneficial AI systems.

The Role

Anthropic is seeking an experienced engineering leader to lead one of our Reliability Engineering teams. This team includes Software Engineers and Systems Engineers focused on defining and achieving reliability metrics for Anthropic\'s critical serving systems. As a manager, you\'ll lead the team that significantly improves reliability for Anthropic\'s services while pioneering the use of modern AI capabilities to reengineer how we approach reliability engineering. This leadership role is critical to Anthropic\'s mission to bring groundbreaking AI technologies to benefit humanity in a safe and reliable way.

Responsibilities

Lead and grow a team of reliability engineers responsible for large language model serving.
Drive the development of Service Level Objectives that balance availability / latency with development velocity across the organization
Oversee the design and implementation of comprehensive monitoring systems for availability, latency and other critical metrics
Guide your team in architecting high-availability language model serving infrastructure capable of supporting millions of external customers and high-traffic internal workloads
Lead the strategy for automated failover and recovery systems across multiple regions and cloud providers
Establish and manage incident response processes for critical AI services, ensuring your team drives rapid recovery and systematic improvements
Direct cost optimization initiatives for large-scale AI infrastructure, with focus on accelerator (GPU / TPU / Trainium) utilization and efficiency
Partner with cross-functional teams to align reliability engineering efforts with broader company objectives
Build a strong engineering culture focused on reliability, operational excellence, and innovation

You May Be a Good Fit If You

Have 5+ years experience managing and scaling reliability or infrastructure engineering teams

Possess deep technical knowledge of distributed systems observability and monitoring at scale

Understand the unique challenges of operating AI infrastructure and can guide technical decisions

Have successfully implemented SLO / SLA frameworks and can drive adoption across organizations

Bring experience with both traditional infrastructure metrics and AI-specific performance indicators

Can effectively lead technical discussions while translating between ML engineers and infrastructure teams

Have excellent leadership and communication skills, with ability to influence at all levels

Demonstrate strong hiring and talent development capabilities

Strong Candidates May Also

Have managed teams operating large-scale model training or serving infrastructure (>

1000 GPUs)

Bring hands-on experience with ML hardware accelerators (GPUs, TPUs, Trainium, etc.)

Understand ML-specific networking optimizations and their operational implications

Have led teams through major reliability transformations or infrastructure migrations

Possess experience building reliability engineering practices from the ground up

Have contributed to or led open-source infrastructure or ML tooling initiatives

Demonstrate thought leadership in the reliability engineering community

Compensation and Logistics

The expected base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.

Annual Salary $405,000 - $485,000 USD

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

Location-based hybrid policy : Currently, we expect all staff to be in one of our offices at least 25% of the time. Some roles may require more time in our offices.

Visa sponsorship : We do sponsor visas. If we make you an offer, we will make every reasonable effort to get you a visa with the assistance of an immigration lawyer.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. We value diverse perspectives and strive to be inclusive in our hiring.

About Anthropic

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a collaborative office environment. Guidance on Candidates\' AI Usage is provided in our application process.

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Engineering Manager Ai • San Francisco, CA, United States