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
- Anthropic is seeking an experienced Infrastructure Engineer to join our Sandboxing team within the Research organization. In this role, you'll build and scale the systems that enable researchers to safely execute and experiment with AI-generated code and interactions in isolated environments.
- As our models become more capable, the infrastructure supporting secure execution environments becomes increasingly critical. You'll work on distributed systems that must operate reliably at significant scale while maintaining strong security boundaries. Your work will directly support Anthropic's mission to develop AI systems that are safe, beneficial, and trustworthy.
Responsibilities
- 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
You may be a good fit if you
- Have 5+ years of experience building and operating backend infrastructure at scale
- Have deep expertise in distributed systems design and implementation
- Have strong operational experience, including debugging complex production issues
- Are proficient with cloud platforms, particularly GCP/GCS (experience with AWS or Azure is also valuable)
- Have experience with containerization technologies (Docker, Kubernetes) and understand their security implications
- Are comfortable working with infrastructure as code and modern DevOps practices
- Have strong programming skills in languages such as Python, Go, or Rust
- Are results-oriented with a bias towards flexibility and impact
- Care about the societal impacts of your work and are motivated by Anthropic's mission
Strong candidates may also have experience with
- Serverless architectures and functions-as-a-service platforms (Cloud Functions, Cloud Run, Lambda)
- Designing and implementing secure multi-tenant systems
- High-performance computing environments or ML infrastructure
- Linux systems internals, including namespaces, cgroups, and seccomp
- Network security and isolation techniques
- Building systems that support research workflows and rapid iteration
- The annual compensation range for this role is listed below.
- For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
How we're different
- We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And 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're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
- The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
