Product Engineer

ABOUT THE ROLE

Join a product engineering team building a platform and marketplace for reinforcement learning environments. You will own end-to-end product challenges that help creators submit and discover work, and help research teams evaluate and improve AI agents.

WHAT YOU'LL DO

• Partner with product, design, engineering, research, and go-to-market teams to identify user friction and prioritize improvements
• Speak directly with environment creators and research teams about creating, testing, evaluating, and discovering reinforcement learning environments
• Design, prototype, and ship improvements across the platform and marketplace, from problem definition through launch and iteration
• Build frontend and backend features for onboarding, submissions, review, and discovery workflows
• Make agent runs, evaluation results, reward signals, and quality feedback easier to understand and act on
• Use user feedback and product data to assess outcomes, refine experiences, and inform tradeoffs

WHAT WE'RE LOOKING FOR

• Experience shipping software products end-to-end, from understanding user needs through implementation and iteration
• Full-stack web application experience, including polished frontend interfaces and backend services or APIs
• Strong product judgment, including identifying underlying problems, setting scope, and making tradeoffs with incomplete information
• Experience interviewing users and applying qualitative feedback and product data to improve shipped products
• Interaction design skills and a focus on clarity and usability in complex technical workflows
• Background in developer tools, data-rich products, marketplaces, or products serving distinct user groups
• Familiarity with AI agents, evaluations, reinforcement learning, training data, or workflows for review, debugging, and quality feedback
• Clear communication and experience working across cross-functional teams

COMPENSATION & BENEFITS

Base salary range: $100,000 to $225,000 USD annually. Visa sponsorship is available.

LOCATION

Remote, with 70% to 80% time zone overlap with San Francisco, California or Singapore. The role is also associated with offices in San Francisco and Singapore.