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.