Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
SQL @ 3
Machine Learning @ 3
Communication @ 3
Prioritization @ 3
Data Analysis @ 3
API @ 3
LLM @ 3
AI @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Anthropic’s 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 computer-use and browser-control product surfaces, building across the full stack from the user interface to the agent runtime and backend services, and working directly alongside researchers.
Responsibilities
- Own end-to-end delivery of computer-use and browser-control product surfaces: scope, build, ship, measure, and iterate
- Diagnose and resolve reliability and robustness issues in the computer-use agent harness that block real-world usage
- Partner with computer-use researchers and the Claude Cowork team on shared surfaces, integrations, and knowledge-worker workflows
- Instrument products and use usage data to drive prioritization and measure progress
- Translate fuzzy user pain points into concrete, shippable features for knowledge workers
Requirements
Minimum qualifications
- Experience building and shipping a product from zero to one with end-to-end ownership (founding/early engineer at a startup or equivalent ownership inside a larger company)
- Strong full-stack engineering skills, including production web frontend and backend development
- Hands-on experience building with LLM APIs, prompting, or agent frameworks
- A track record of shipping to external users and iterating based on their feedback
- Minimum education: Bachelor’s degree or equivalent combination of education, training, and/or experience
Preferred qualifications
- Strong product design instincts and ability to produce a clean, usable interface without a dedicated designer
- Experience with browser automation, desktop automation, or robotic process automation systems
- Experience building evals or quality harnesses for machine learning systems
- Comfort with lightweight data analysis (SQL, notebooks) and defining/tracking product metrics
- Experience designing agent loops, tool integrations, or guardrails for LLM-based systems
Representative projects
- Resolve the top reliability and robustness issues on the computer-control and browser-control product surfaces, with measurable improvement in task success rate
- Take a net-new computer-use powered workflow from concept to external users, including instrumentation and a readout on usage
Compensation
- Annual salary range: $300,000 - $320,000 USD
Logistics
- Locations: San Francisco, CA and Seattle, WA (United States)
- Location-based hybrid policy: staff expected to be in one of the offices at least 25% of the time
- Minimum years of experience: will correlate with internal job level requirements
Benefits
- Competitive compensation and benefits
- Optional equity donation matching
- Generous vacation and parental leave
- Flexible working hours and a collaborative office space
Visa
- Anthropic states they sponsor visas and retain an immigration lawyer; they note sponsorship is not guaranteed for every role/candidate but they will make reasonable efforts if an offer is made.
How we're different
- Small number of large-scale research efforts, collaborative environment, emphasis on communication and high-impact AI research. The posting references Anthropic's research directions and publications.