Infrastructure Engineer - Sandboxing Team (Remote)
About the Role
We are looking for an experienced Infrastructure Engineer to join our Sandboxing team at Anthropic. This Infrastructure Engineer remote position will focus on building and scaling systems that allow researchers to safely execute AI-generated code in isolated environments. As AI models become more capable, the need for secure execution environments becomes increasingly critical. You will be instrumental in supporting Anthropic's mission to develop safe and beneficial AI systems.
What You'll Do
- Design, build, and operate distributed backend systems that power secure sandboxed execution environments.
- Scale infrastructure to meet growing research and product demands while maintaining reliability and performance.
- Implement and maintain serverless architectures and container orchestration systems.
- Collaborate with research teams to understand requirements and translate them into robust infrastructure solutions.
- Develop monitoring, alerting, and observability systems to ensure operational excellence.
- Participate in on-call rotations and incident response to maintain system reliability.
- Contribute to infrastructure automation and tooling that improves developer productivity.
- Partner with security teams to ensure sandboxing infrastructure maintains appropriate isolation guarantees.
Requirements
- 5+ years of experience building and operating backend infrastructure at scale.
- Deep expertise in distributed systems design and implementation.
- Strong operational experience, including debugging complex production issues.
- Proficient with cloud platforms, particularly GCP/GCS (AWS or Azure experience is also valuable).
- Experience with containerization technologies (Docker, Kubernetes) and understanding their security implications.
- Comfortable working with infrastructure as code and modern DevOps practices.
- Strong programming skills in languages such as Python, Go, or Rust.
- Results-oriented with a bias towards flexibility and impact.
Nice to Have
- Experience with serverless architectures and functions-as-a-service platforms.
- Designing and implementing secure multi-tenant systems.
- High-performance computing environments or ML infrastructure experience.
- Familiarity with Linux systems internals, including namespaces, cgroups, and seccomp.
- Knowledge of network security and isolation techniques.
What We Offer
- Annual salary range of $300,000—$405,000 USD.
- Hybrid work policy with 25% office time.
- Visa sponsorship available.
- Generous vacation and parental leave.
- Flexible working hours.
- Collaborative office environment in San Francisco.
Join us at Anthropic and contribute to our mission of creating reliable and beneficial AI systems. Apply now for this exciting Infrastructure Engineer remote position!
This Infrastructure Engineer role at Anthropic offers a unique opportunity to work on cutting-edge AI systems in a collaborative environment. With a competitive salary and flexible work arrangements, it's an attractive position for skilled engineers.
About Anthropic
Explore Anthropic careers in 2026 and discover exciting job opportunities across remote, hybrid, and office roles. Our platform offers advanced filters to refine your search, application tracking to streamline your process, and valuable company insights to help you succeed. Stay ahead in your job search for Anthropic positions and unlock your potential in the innovative tech landscape.
Who Will Succeed Here
Proficiency in distributed systems architecture, with hands-on experience in container orchestration using Docker and Kubernetes, to effectively manage and scale isolated environments for AI execution.
Strong familiarity with cloud platforms (GCP, AWS, Azure) and their security frameworks, enabling the design and implementation of secure execution environments for AI-generated code.
A proactive mindset towards problem-solving and continuous learning, with a focus on emerging technologies like Rust and Go, to enhance system performance and maintainability in a remote work setting.
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