Software Engineer, Sandboxing
San Francisco, CA | New York City, NYFull-TimeMid-levelSoftware Engineering
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's sandboxing infrastructure enables Claude to safely execute code and interact with external systems. As we expand Claude's capabilities, the reliability, security, and developer experience of this infrastructure becomes increasingly critical. We're looking for an engineer to join the sandboxing team and help shape both the client-side library/API and the underlying infrastructure.
- In this role, you'll combine deep infrastructure expertise with an obsession for developer experience. You'll help maintain and evolve a system that must be correct, performant, and intuitive to use. You'll work closely with internal teams to understand their needs, burn down errors and edge cases, and build a roadmap that anticipates where the product needs to go. This is a role for someone who finds satisfaction in both the craft of building reliable systems and the empathy required to serve developers and researchers well.
Responsibilities
- Contribute to the client library, API surface, and underlying infrastructure for Anthropic's sandboxing system, ensuring it is reliable, well-documented, and intuitive to use
- Drive down error rates and improve correctness through systematic debugging, monitoring, and proactive fixes
- Help develop and maintain a product roadmap for sandboxing capabilities, balancing immediate needs with long-term architectural improvements
- Partner closely with internal teams using the sandboxing system to understand their requirements, debug issues, and build tooling that serves their use cases
- Respond to incidents and production issues with urgency, conducting thorough root cause analysis and implementing preventive measures
- Build comprehensive testing, observability, and documentation to ensure the system meets a high quality bar
- Collaborate across the sandboxing team, flexing between client-side and infrastructure work as needed
- Contribute to the client library, API surface, and underlying infrastructure for Anthropic's sandboxing system, ensuring it is reliable, well-documented, and intuitive to use
- Drive down error rates and improve correctness through systematic debugging, monitoring, and proactive fixes
- Help develop and maintain a product roadmap for sandboxing capabilities, balancing immediate needs with long-term architectural improvements
- Partner closely with internal teams using the sandboxing system to understand their requirements, debug issues, and build tooling that serves their use cases
- Respond to incidents and production issues with urgency, conducting thorough root cause analysis and implementing preventive measures
- Build comprehensive testing, observability, and documentation to ensure the system meets a high quality bar
- Collaborate across the sandboxing team, flexing between client-side and infrastructure work as needed
You May Be a Good Fit If You
- Have 5+ years of software engineering experience, with meaningful time spent maintaining libraries, SDKs, or developer-facing APIs
- Obsess over developer experience—you've thought deeply about API design, error propagation, documentation, and the small details that make a library feel well-crafted
- Have experience operating complex distributed systems
- Bring a track record of systematically improving reliability—you've burned down error budgets, built monitoring, and driven issues to resolution
- Can develop and articulate a long-term vision for a product, translating user feedback and technical constraints into a coherent roadmap
- Are comfortable with ambiguity and can context-switch between reactive incident work and proactive product development
- Communicate clearly with both technical and non-technical stakeholders
- Have 5+ years of software engineering experience, with meaningful time spent maintaining libraries, SDKs, or developer-facing APIs
- Obsess over developer experience—you've thought deeply about API design, error propagation, documentation, and the small details that make a library feel well-crafted
- Have experience operating complex distributed systems
- Bring a track record of systematically improving reliability—you've burned down error budgets, built monitoring, and driven issues to resolution
- Can develop and articulate a long-term vision for a product, translating user feedback and technical constraints into a coherent roadmap
- Are comfortable with ambiguity and can context-switch between reactive incident work and proactive product development
- Communicate clearly with both technical and non-technical stakeholders
Strong Candidates May Also Have
- Experience as a founder or early engineer at an infrastructure-focused startup, where you owned a product end-to-end
- Background in security, sandboxing, or isolation technologies (containers, VMs, seccomp, namespaces, etc.)
- Open-source contributions in the Python ecosystem
- Experience building developer tools, CLIs, or platforms used by other engineers
- History of working on incident response and on-call rotations for production systems
- Exposure to reinforcement learning or model training infrastructure
- Experience as a founder or early engineer at an infrastructure-focused startup, where you owned a product end-to-end
- Background in security, sandboxing, or isolation technologies (containers, VMs, seccomp, namespaces, etc.)
- Open-source contributions in the Python ecosystem
- Experience building developer tools, CLIs, or platforms used by other engineers
- History of working on incident response and on-call rotations for production systems
- Exposure to reinforcement learning or model training infrastructure
Representative Projects
- These are examples of past work that would indicate a good fit—not a description of the role itself:
- Maintaining an open source SDK through multiple major version upgrades while minimizing breaking changes for users
- Leading an initiative to reduce P0 incidents by XX% through improved error handling, retries, and observability
- Building a developer platform at a startup from zero to product-market fit, iterating based on user feedback
- Embedding with an internal team for a quarter to deeply understand their workflows and shipping targeted improvements to a piece of infrastructure they rely on
- Developing a multi-quarter roadmap for a developer tools product, balancing user requests with technical debt reduction
- Maintaining an open source SDK through multiple major version upgrades while minimizing breaking changes for users
- Leading an initiative to reduce P0 incidents by XX% through improved error handling, retries, and observability
- Building a developer platform at a startup from zero to product-market fit, iterating based on user feedback
- Embedding with an internal team for a quarter to deeply understand their workflows and shipping targeted improvements to a piece of infrastructure they rely on
- Developing a multi-quarter roadmap for a developer tools product, balancing user requests with technical debt reduction
- 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.
