Staff + Sr. Software Engineer, Inference Deployment
Anthropic · San Francisco, CA | New York City, NY | Seattle, WA · Software Engineering - Infrastructure
About this role
Anthropic is hiring a senior-level Software Engineer based in San Francisco, CA | New York City, NY | Seattle, WA. The posting calls out experience with Python, Rust, Kubernetes, CI/CD. Compensation is listed at $320,000–$485,000 per year.
- Role
- Software Engineer
- Function
- software engineering
- Level
- senior
- Track
- Tech leadership
- Employment
- Full-time
- Location
- San Francisco, CA | New York City, NY | Seattle, WA
- Department
- Software Engineering - Infrastructure
More roles at Anthropic
Job description
from Anthropic careersAbout 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
Our mandate is to make inference deployment boring and unattended.
Anthropic serves Claude to millions of users across GPUs, TPUs, and Trainium — and every model update must reach production safely, quickly, and without disrupting service. We're building the systems that make inference deployment continuous and unattended.
As a Software Engineer on the Launch Engineering team, you'll design and build the deployment infrastructure that moves inference code from merge to production. This is a resource-constrained optimization problem at its core: validation and deployment consume the same accelerator chips that serve customer traffic — your deploys compete with live user requests for the same hardware. Every model brings different fleet sizes, startup times, and correctness requirements, so the system must adapt continuously. You'll build systems that navigate these constraints — orchestrating validation, scheduling deployments intelligently, and driving down cycle time from merge to production.