Senior AI Software Engineer

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.

Our Inference team is responsible for building and maintaining 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. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators.

The team has a dual mandate:

• maximising compute efficiency to serve our explosive customer growth
• enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models

We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms.

Key responsibilities include:

• High-performance, large-scale distributed systems
• Implementing and deploying machine learning systems at scale
• Kubernetes and cloud infrastructure (AWS, GCP)
• Python or Rust
• Significant software engineering experience, particularly with distributed systems
• Desire to learn more about machine learning systems and infrastructure

Representative projects across the organisation:

• Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads
• Building production-grade deployment pipelines for releasing new models to millions of users
• Integrating new AI accelerator platforms to maintain our hardware-agnostic competitive advantage
• Analysing observability data to tune performance based on real-world production workloads
• Managing multi-region deployments and geographic routing for global customers

Required qualifications:

• Bachelor’s degree or an equivalent combination of education, training, and/or experience
• Field of study relevant to the role as demonstrated through coursework, training, or professional experience

Location-based hybrid policy: Visa sponsorship available, but not guaranteed for every role and candidate.

We think AI systems like the ones we're building have enormous social and ethical implications. We believe that the highest-impact AI research will be big science. We value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science.

We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.