Staff Senior Software Engineer (AI)

TL;DR

Staff Senior Software Engineer (AI): Designing and building deployment infrastructure to move inference code from merge to production with an accent on capacity-aware scheduling and resource-constrained optimization. Focus on orchestrating validation, driving down cycle time, and optimizing rollout strategies across GPU, TPU, and Trainium fleets.

Location: Hybrid (San Francisco, New York City, or Seattle); must be in office at least 25% of the time

Salary: $320,000 – $485,000 USD

Company

Anthropic is a public benefit corporation dedicated to creating reliable, interpretable, and steerable AI systems that are safe and beneficial for society.

What you will do

• Own deployment orchestration to move validated inference builds into production across GPU, TPU, and Trainium fleets.
• Improve capacity-aware deployment scheduling to maximize throughput against constrained accelerator budgets.
• Develop deployment observability tools and dashboards to track code status and validation results.
• Architect pipelines to minimize serial dependencies and maximize parallelism to reduce merge-to-production cycle time.
• Optimize fleet rollout strategies for large-scale deployments across thousands of accelerator chips.
• Evolve self-service model onboarding to enable continuous deployment without manual intervention.

Requirements

• Experience designing systems for complex state machines and multi-stage pipelines.
• Proficiency with Kubernetes-based deployments, container orchestration, and rolling update mechanics.
• Experience building delivery infrastructure where resource constraints (capacity, bandwidth) shape the design.
• Proven track record of building automation that measurably improves deployment velocity and reliability.
• Comfort working across the stack, from backend services and databases to CLI tools and web UIs.
• Bachelor's degree or equivalent combination of education and professional experience.

Nice to have

• 5+ years of experience building large-scale deployment or release infrastructure.
• Production experience with Python and/or Rust.
• Experience with ML inference or training infrastructure deployment across multiple accelerator types.
• Background in capacity planning, bin-packing, or resource-constrained scheduling.
• Experience with progressive delivery, such as canary/soak testing and blue-green deployments.

Culture & Benefits

• Competitive compensation and benefits with optional equity donation matching.
• Generous vacation and parental leave.
• Flexible working hours and high-quality collaborative office spaces.
• Visa sponsorship available for eligible candidates.