Anthropic · 2 hours ago
Staff + Senior Software Engineer, Cloud Inference
San Francisco, CA
Full-time
Hybrid
Senior Level, Lead/Staff
$300K/yr - $485K/yrAnthropic is a public benefit corporation committed to creating reliable and beneficial AI systems. The Staff + Senior Software Engineer, Cloud Inference will design and build infrastructure for serving AI models across multiple cloud service providers, ensuring efficient management and optimization of resources to support large-scale operations.
Artificial Intelligence (AI)Foundational AIGenerative AIInformation TechnologyMachine Learning
Responsibilities
Design and build infrastructure that serves Claude across multiple CSPs, accounting for differences in compute hardware, networking, APIs, and operational models
Collaborate with CSP partner engineering teams to resolve operational issues, influence provider roadmaps, and stand up end-to-end serving on new cloud platforms
Design and evolve CI/CD automation systems, including validation and deployment pipelines, that reliably ship new model versions to millions of users across cloud platforms without regressions
Design interfaces and tooling abstractions across CSPs that enable cost-effective inference management, scale across providers, and reduce per-platform complexity
Contribute to capacity planning and autoscaling strategies that dynamically match supply with demand across CSP validation and production workloads
Optimize inference cost and performance across providers—designing workload placement and routing systems that direct requests to the most cost-effective accelerator and region
Contribute to inference features that must work consistently across all platforms
Analyze observability data across providers to identify performance bottlenecks, cost anomalies, and regressions, and drive remediation based on real-world production workloads
Qualification
Required
Have significant software engineering experience, with a strong background in high-performance, large-scale distributed systems serving millions of users
Have experience building or operating services on at least one major cloud platform (AWS, GCP, or Azure), with exposure to Kubernetes, Infrastructure as Code or container orchestration
Have strong interest in inference
Thrive in cross-functional collaboration with both internal teams and external partners
Are a fast learner who can quickly ramp up on new technologies, hardware platforms, and provider ecosystems
Are highly autonomous and self-driven, taking ownership of problems end-to-end with a bias toward flexibility and high-impact work
Pick up slack, even when it goes outside your job description
Design and build infrastructure that serves Claude across multiple CSPs, accounting for differences in compute hardware, networking, APIs, and operational models
Collaborate with CSP partner engineering teams to resolve operational issues, influence provider roadmaps, and stand up end-to-end serving on new cloud platforms
Design and evolve CI/CD automation systems, including validation and deployment pipelines, that reliably ship new model versions to millions of users across cloud platforms without regressions
Design interfaces and tooling abstractions across CSPs that enable cost-effective inference management, scale across providers, and reduce per-platform complexity
Contribute to capacity planning and autoscaling strategies that dynamically match supply with demand across CSP validation and production workloads
Optimize inference cost and performance across providers—designing workload placement and routing systems that direct requests to the most cost-effective accelerator and region
Contribute to inference features that must work consistently across all platforms
Analyze observability data across providers to identify performance bottlenecks, cost anomalies, and regressions, and drive remediation based on real-world production workloads
Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience
Preferred
Direct experience working with CSP partner teams to scale infrastructure or products across multiple platforms, navigating differences in networking, security, privacy, billing, and managed service offerings
A background in building platform-agnostic tooling or abstraction layers that work across cloud providers
Hands-on experience with capacity management, cost optimization, or resource planning at scale across heterogeneous environments
Strong familiarity with LLM inference optimization, batching, caching, and serving strategies
Experience with Machine learning infrastructure including GPUs, TPUs, Trainium, or other AI accelerators
Background designing and building CI/CD systems that automate deployment and validation across cloud environments
Solid understanding of multi-region deployments, geographic routing, and global traffic management
Proficiency in Python or Rust
Benefits
Optional equity donation matching
Generous vacation and parental leave
Flexible working hours
Company
Anthropic
Anthropic is an AI research company that focuses on the safety and alignment of AI systems with human values.
Founded in 2021
501-1000 employees
H1B Sponsorship
Anthropic has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (105)
2024 (13)
2023 (3)
2022 (4)
2021 (1)
Funding
Current Stage
Late StageTotal Funding
$33.74BKey Investors
Lightspeed Venture PartnersGoogleAmazon
2025-09-02Series F· $13B
2025-05-16Debt Financing· $2.5B
2025-03-03Series E· $3.5B
Leadership Team
Dario Amodei
Co-Founder and CEO
Daniela Amodei
President and co-founder
Recent News
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