AI Product Owner

Fuse Energy is an energy startup on a mission to make energy abundant and affordable, fast. We combine first-principles thinking with cutting-edge technology to build a radically better energy system.

We've raised over $200M from top-tier investors including Balderton, Lakestar, Accel, Creandum, Lowercarbon, Ribbit, 20VC, Hummingbird and Collaborative Fund, alongside strategic angels including Nico Rosberg and GPs behind Meta, Revolut, Spotify and Uber.

We're building a fully integrated energy company: developing our own solar, batteries and other generation projects, building our own hardware, improving and developing grid infrastructure, trading power in real time, using AI across the business, and installing distributed energy in homes. By selling directly to consumers we cut out the middleman, lower costs and pass the savings on to our customers.

This isn't a traditional product role. AI Engineers at Fuse are shipping real, customer-facing systems across the business. You'll own the product side of this work: sitting close to the engineers, turning ambiguous, high-impact problems into scoped projects, owning the roadmap, and being the bridge between engineering and the rest of the business.

• →Own the product roadmap for Fuse's AI initiatives end-to-end, from identifying high-impact problems to scoping, prioritizing and shipping solutions
• →Partner day-to-day with AI Engineers on live projects spanning customer operations, data labeling and collection, and other business functions
• →Translate ambiguous problems from trading, customer operations, and internal tooling into clear, scoped projects with defined success metrics
• →Build and manage the backlog for AI engineering, balancing speed, data/model quality, and business impact
• →Define how AI systems are evaluated in production, and drive the feedback loops that keep improving them post-launch

• Bachelor's degree from a top university in STEM
• Experience as a product owner, product manager, or technical program manager on engineering-heavy, ideally AI/ML or data-heavy, products
• Deep curiosity about AI and a track record of using it in real-world settings
• Comfortable working directly with engineers, translating between technical and business teams without losing precision on either side
• Relentless approach to solving problems, and comfortable operating with ambiguity