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Software Engineer, Sandboxing

Anthropic

San Francisco, CA | New York City, NY · San Francisco · USD 320,000-485,000 / year · Hybrid · Posted Oct 1, 2026

At a glance

Workplace
Hybrid
Location
San Francisco, CA | New York City, NY · San Francisco
Salary
USD 320,000-485,000 / year · Base salary
Visa sponsorship
Visa sponsorship available

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

  • Every time Claude runs code, uses a computer, or works as an agent, it does so inside a sandbox built by the Sandboxing team.
  • The role involves building the isolation layer that runs untrusted, model-generated code, training environments, and customer-deployed agents.
  • You will work at the boundary between the Linux kernel, virtualization, and the container ecosystem to ensure safe and fast systems.

Responsibilities

  • Design, build, and operate the sandboxing infrastructure that runs untrusted, model-generated code and agent workloads at scale
  • Improve sandbox startup time, density, and throughput, including snapshot and restore, checkpointing, and warm pools
  • Strengthen isolation across compute, filesystem, and network, including egress controls and per-session credential handling
  • Investigate and fix performance, reliability, and security issues at the kernel, hypervisor, and container runtime level
  • Build the monitoring, tracing, and debugging tools that show where time and resources go inside a sandbox
  • Work with researchers to support reinforcement learning environments and evaluations that need fast, reproducible, isolated execution
  • Work with product and platform engineers to expose sandboxes as a dependable, well-designed capability for Claude products and customers
  • Partner with security teams to threat-model the platform and to test, harden, and respond to escape and abuse scenarios
  • Work with cloud providers on the hardware and platform features that our workloads depend on
  • Share knowledge on systems programming and Linux internals, and help set technical standards for the team

Requirements

  • Software engineering experience in Linux systems programming, kernel development, or another low-level area
  • Strong programming skills in at least one systems language such as Rust, C, C++, or Go
  • Working knowledge of virtualization or container isolation technologies such as KVM, QEMU, Firecracker, gVisor, or runc
  • Understanding of Linux resource management, including namespaces, cgroups, scheduling, and memory management
  • Experience profiling and debugging performance issues at the system level
  • Ability to work in unfamiliar codebases and technical areas, and to ship practical solutions with measurable results
  • Strong communication skills and a commitment to building safe, reliable systems
  • Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
  • Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Preferred qualifications

  • Experience building or operating a multi-tenant sandbox, serverless, or code execution platform
  • Experience with microVMs, user-space kernels, or lightweight virtualization, including snapshot and restore
  • Experience with OS-level security hardening, including seccomp, LSMs, and threat modeling of untrusted code
  • Experience with eBPF and kernel tracing tools
  • Experience with Kubernetes and cloud infrastructure at scale (AWS, GCP)
  • Experience with network isolation, high-performance networking, or building egress proxies and policy layers
  • Experience with sandboxes for AI agents, computer use, or reinforcement learning environments
  • Experience with GPU virtualization, accelerators, or performance work on machine learning workloads

Benefits

  • Competitive compensation and benefits
  • Optional equity donation matching
  • Generous vacation
  • Parental leave
  • Flexible working hours

Workplace

  • Location-based hybrid policy expecting staff to be in one of the offices at least 25% of the time

Skills

  • Rust
  • C
  • C++
  • Go
  • KVM
  • QEMU
  • Firecracker
  • gVisor
  • Runc
  • Kubernetes
  • AWS
  • GCP
Show all 13 skills
  • eBPF

Anthropic

Software Engineer, Sandboxing

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