Staff + Senior Software Engineer (Inference Deployment)
Company: Anthropic
Location: San Francisco, CA | New York City, NY | Seattle, WA
Salary: $320k - $485k per year
Type: Full-time
Posted: 2026-07-09
About this role
- 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
- The Launch Engineering team’s mandate is to make inference deployment boring and unattended
- As a Software Engineer on Launch Engineering, 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, so your deploys compete with live user requests for the same hardware
- Every model brings different fleet sizes, startup times, and correctness requirements, and 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
- Own deployment orchestration that continuously moves validated inference builds into production across GPU, TPU, and Trainium fleets, unattended under normal conditions
- Improve capacity-aware deployment scheduling to maximize deployment throughput against constrained accelerator budgets and variable fleet sizes
- Extend deployment observability — dashboards and tooling that answer “what code is running in production,” “where is my commit,” and “what validation passed for this deploy”
- Drive down cycle time from code merge to production with pipeline architectures that minimize serial dependencies and maximize parallelism
- Optimize fleet rollout strategies for large-scale deployments across thousands of accelerator chips, minimizing disruption to serving capacity
- Evolve self-service model onboarding so new models can be added to the continuous deployment pipeline without Launch Engineering involvement
- Partner across the Inference organization with teams owning validation, autoscaling, and model routing to integrate deployment...