Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Security @ 4
Go @ 4
Linux @ 4
Python @ 4
GCP @ 4
Airflow @ 3
Distributed Systems @ 8
AWS @ 4
Azure @ 4
Communication @ 4
Rust @ 4
Debugging @ 4
Observability @ 4
AI @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. Claude App Infrastructure is the platform team for Anthropic's flagship consumer product (claude.ai) responsible for the serving architecture, conversation experience, and infrastructure that enables product teams to ship into claude.ai safely and quickly. The team owns reliability, experience, and agentic capabilities, and is building the agentic layer that enables task execution, personalization, browser use, and server-side tools.
Responsibilities
- Design and build sandboxed compute environments where Claude can safely execute code, access tools, and interact with external services.
- Build state management systems for long-running agent tasks—handling checkpoints, recovery, and resumption across failures.
- Develop authentication and authorization frameworks for delegated access—enabling Claude to act on behalf of users securely.
- Create observability and debugging tools for agent execution—understanding what Claude did, why, and how to make it better.
- Partner closely with product and research teams to define what's possible and ship features.
Requirements
- 10+ years of experience building distributed systems, infrastructure, or platform services at hyper scale.
- Comfortable building Cloud Native infrastructure on GCP, AWS, or Azure.
- Care deeply about security, isolation, and building systems that fail safely.
- Experience with containers, sandboxing, or secure execution environments (examples cited: gVisor, Firecracker, V8 isolates).
- Comfortable with ambiguity—greenfield work where you will help define the architecture.
- Write clean, maintainable code in Python, Go, Rust, or similar languages.
Strong candidates may have
- Experience building multi-tenant execution platforms or serverless infrastructure.
- Background in security engineering, sandboxing, or isolation technologies.
- Familiarity with workflow orchestration systems (Temporal, Airflow, Step Functions).
- Experience with state machines, checkpointing, or durable execution patterns.
- Low-level systems experience (Linux internals, eBPF, container runtimes).
Compensation
- Annual Salary: $320,000 - $485,000 USD
Logistics
- Education requirements: At least a Bachelor's degree in a related field or equivalent experience.
- Location-based hybrid policy: Expectation that all staff are in one of Anthropic's offices at least 25% of the time; some roles may require more time in office.
- Visa sponsorship: Anthropic states they do sponsor visas and retain an immigration lawyer to assist, though sponsorship may not be possible for every role/candidate.
About Anthropic
- Anthropic is a public benefit corporation headquartered in San Francisco. The company emphasizes collaborative, large-scale AI research, and values communication skills and diverse perspectives.