About Anthropic
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.
About the role:
Anthropic is seeking an experienced engineering leader to manage our Reliability Engineering team. This team includes Software Engineers and Systems Engineers focused on defining and achieving reliability metrics for all of Anthropic's internal and external products and services. As a manager, you'll lead the team that's significantly improving 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 and training systems
- Drive the development of service level objectives (SLOs) 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 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
The expected salary range for this position is:
Annual Salary:
€295.000—€355.000 EUR
Logistics
**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. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
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. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
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 lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process