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

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

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

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

Logistics

• 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
• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
• Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

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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

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

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

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

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building can have a huge impact on society, and we want to make sure that the people building them are representative of the people they'll be serving.

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As a Research Engineer on our team, you will work end to end across the whole model stack, identifying and addressing key infra blockers on the path to scientific AGI. Strong candidates should have familiarity with elements of language model training, evaluation, and inference and eagerness to quickly dive and get up to speed in areas they are not yet an expert on. This may include performance optimization, distributed systems, VM/sandboxing/container deployment, and large scale data pipelines.

Responsibilities:

• Design and implement large-scale infrastructure systems to support AI scientist training, evaluation, and deployment across distributed environments
• Identify and resolve infrastructure bottlenecks impeding progress toward scientific capabilities
• Develop robust and reliable evaluation frameworks for measuring progress towards scientific AGI.
• Build scalable and performant VM/sandboxing/container architectures to safely execute long-horizon AI tasks and scientific workflows
• Collaborate to translate experimental requirements into production-ready infrastructure
• Develop large scale data pipelines to handle advanced language model training requirements
• Optimize large scale training and inference pipelines for stable and efficient reinforcement learning

You may be a good fit if you:

• Have 6+ years of highly-relevant experience in infrastructure engineering with demonstrated expertise in large-scale distributed systems
• Are a strong communicator and enjoy working collaboratively
• Possess deep knowledge of performance optimization techniques and system architectures for high-throughput ML workloads
• Have experience with containerization technologies (Docker, Kubernetes) and orchestration at scale
• Have proven track record of building large-scale data pipelines and distributed storage systems
• Excel at diagnosing and resolving complex infrastructure challenges in production environments
• Can work effectively across the full ML stack from data pipelines to performance optimization
• Have experience collaborating with other researchers to scale experimental ideas
• Thrive in fast-paced environments and can rapidly iterate from experimentation to production

Strong candidates may also have:

• Experience with language model training infrastructure and distributed ML frameworks (PyTorch, JAX, etc.)
• Background in building infrastructure for AI research labs or large-scale ML organizations
• Knowledge of GPU/TPU architectures and language model inference optimization
• Experience with cloud platforms (AWS, GCP) at enterprise scale
• Familiarity with VM and container orchestration.
• Experience with workflow orchestration tools and experiment management systems
• History working with large scale reinforcement learning
• Comfort with large scale data pipelines (Beam, Spark, Dask, …)

Logistics

• Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.
• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
• Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

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 projects, and we're committed to making a positive impact on the world.

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