Staff + Sr. Software Engineer, Scaling
New York City, NY · San Francisco · Seattle, WA · USD 320,000-485,000 / year · Hybrid · Posted Sep 28, 2026
At a glance
- Workplace
- Hybrid
- Location
- New York City, NY · San Francisco · Seattle, WA
- Salary
- USD 320,000-485,000 / year · Base salary
- Visa sponsorship
- Visa sponsorship available
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
- Our Inference team is responsible for building and scaling the critical systems that serve Claude to millions of users worldwide.
- We bring Claude to life by serving our models via the industry’s largest compute-agnostic inference deployments.
- The team has a dual mandate: maximizing compute efficiency to reliably serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models.
Responsibilities
- Design, build, and maintain the distributed systems that serve Claude to millions of users worldwide
- Develop resilient, flexible systems that adapt in real time to real world events
- Develop intelligent request routing, load balancing, and traffic management systems across thousands of accelerators and multiple cloud providers
- Maximize compute efficiency and optimize cost across the fleet by autoscaling and orchestrating production, research, and experimental workloads across multiple cloud providers
- Build and operate production-grade deployment pipelines for releasing new models to users
- Provide high-performance inference infrastructure that enables researchers to develop next-generation models
- Integrate new AI accelerator platforms and support inference for new model architectures
Requirements
- Significant software engineering experience, particularly with distributed systems
- Results-oriented, with a bias towards flexibility and impact
- Willingness to pick up slack, even if it goes outside your job description
- Desire to learn more about machine learning systems and infrastructure
- Thrive in environments where technical excellence directly drives both business results and research breakthroughs
- Care about the societal impacts of your work
- Bachelor’s degree or an equivalent combination of education, training, and/or experience
- A field of study relevant to the role as demonstrated through coursework, training, or professional experience
Preferred qualifications
- Experience with high-performance, large-scale distributed systems
- Experience implementing and deploying machine learning systems at scale
- Experience with load balancing, request routing, or traffic management systems
- Familiarity with LLM inference optimization, batching, and caching strategies
- Experience with Kubernetes and cloud infrastructure (AWS, GCP, Azure)
- Proficiency in Python or Rust
Benefits
- Competitive compensation and benefits
- Optional equity donation matching
- Generous vacation
- Parental leave
- Flexible working hours
Workplace
- Location-based hybrid policy expecting all staff to be in one of the offices at least 25% of the time
Skills
- Python
- Rust
- Kubernetes
- AWS
- GCP
- Azure
