Anthropic· Software Engineering - Infrastructure· San Francisco, CA | Seattle, WA
Engineering Manager, Cloud Inference AWS
Classified Tasks (14)
Automate 0%Augment 50%Human-Only 50%
Augment (7)
AI assists, human decides
2. Scale and optimize Claude on AWS to serve large audiences of developers and enterprise customers.
technical
3. Own the end-to-end product of Claude on AWS, including API, load balancing, inference, capacity, and operations.
operational
6. Identify and propose solutions to support frontier LLM serving.
technical
11. Design and run processes such as postmortem reviews, incident response, and on-call rotations.
operational
12. Ensure LLMs meet rigorous performance, safety, and security standards.
technical
13. Enhance core infrastructure for packaging, testing, and deploying inference technology globally.
technical
14. Increase operational scale and accelerate reliable launches of new models and features across platforms.
operational
Human-Only (7)
Requires human judgment
1. Lead the Cloud Inference team for AWS.
leadership
4. Set technical strategy and oversee development of Claude on AWS across all layers of the technical stack.
leadership
5. Collaborate across teams and companies to deeply understand product, infrastructure, operations, and capacity needs.
communication
7. Work closely with cross-functional stakeholders to align on goals and drive outcomes.
communication
8. Create clarity for the team and stakeholders in ambiguous and evolving environments.
leadership
9. Hire top technical talent using an inclusive approach.
leadership
10. Coach engineering talent and support a high-performing team.
leadership
Job description
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 We are seeking an experienced Engineering Manager to lead the Cloud Inference team for AWS. You will lead your team to scale and optimize Claude to serve the massive audiences of developers and enterprise companies using AWS. You will own the end-to-end product of Claude on AWS, including API, load balancing, inference, capacity and operations. Your team will ensure our LLMs meet rigorous performance, safety and security standards and enhance our core infrastructure for packaging, testing, and deploying inference technology across the globe. Your work will increase the scale at which Anthropic operates and accelerate our ability to reliably launch new frontier models and innovative features to customers across all platforms. Responsibilities: Set technical strategy and oversee development of Claude on AWS across all layers of the technical stack. Collaborate across teams and companies to deeply understand product, infrastructure, operations and capacity needs, identifying potential solutions to support frontier LLM serving Work closely with cross-functional stakeholders across companies to align on goals and drive outcomes Create clarity for the team and stakeholders in an ambiguous and evolving environment Take an inclusive approach to hiring and coaching top technical talent, and support a high performing team Design and run processes (e.g. postmortem review, incident response, on-call rotations) that help the team operate effectively and never fail the same way twice You may be a good fit if you: Have 10+ years of experience in high-scale, high-reliability software development, particularly infrastructure or capacity management Have 5+ years of engineering management experience Experience recruiting, scaling, and retaining engineering talent in a high growth environment Have experience scaling products, resources and operations to accommodate rapid growth Are deeply interested in the potential transformative effects of advanced AI systems and are committed to ensuring their safe development Excel at building strong relationships and strategy with stakeholders across engineering, product, finance, and sales Have experience working with external partners to align goals and deliver impact Enjoy working in a fast-paced, early environment; comfortable with adapting priorities as driven by the rapidly evolving AI space Have excellent written and verbal communication skills Demonstrated success building a culture of belonging and engineering excellence Are motivated by developing AI responsibly and safely Are willing and able to travel frequently between Seattle and the SF Bay Area Strong candidates may also have experience with: Experience with machine learning infrastructure like GPUs, TPUs, or Trainium, as well as supporting networking infrastructure like NCCL Experience as a Product Manager Experience with deployment and capacity management automation <li class="heading"