Product Engineer, Computer Use
AnthropicAbout 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
The Computer Use team teaches Claude to see and operate computer interfaces, and builds the agent harness and end-user products that turn that capability into real tools. The team sits inside Anthropic's research organization and closes the loop between product and model.
As a Product Engineer on this team, you'll own end-to-end delivery of our computer-use and browser-control product surfaces. You'll build across the full stack, from the user interface to the agent runtime to the backend services behind it. You'll work directly alongside researchers, with no layers between you and the model or the user.
This is a dynamic role in which priorities evolve frequently. Success depends on a high tolerance for ambiguity, the adaptability to shift focus as needs change, and the agility and discernment to continuously prioritize the highest impact work.
Key responsibilities
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Own end-to-end delivery of computer-use and browser-control product surfaces: scope, build, ship, measure, and iterate
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Diagnose and resolve reliability and robustness issues in the computer-use agent harness that block real-world usage
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Partner with computer-use researchers
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Partner with the Claude Cowork team on shared surfaces, integrations, and knowledge-worker workflows
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Instrument products and use usage data to drive prioritization and measure progress
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Translate fuzzy user pain points into concrete, shippable features for knowledge workers
Minimum qualifications
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Experience building and shipping a product from zero to one with end-to-end ownership, as a founding or early engineer at a startup or with equivalent ownership inside a larger company
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Strong full-stack engineering skills, including production web frontend and backend development
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Hands-on experience building with LLM APIs, prompting, or agent frameworks
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A track record of shipping to external users and ite
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