Fuse Energy is a forward-thinking renewable energy startup on a mission to deliver a terawatt of renewable energy - fast. We're combining first-principles thinking with cutting-edge technology to build a radically better energy system. We raised $170M from top-tier investors including Multicoin, Balderton, Lakestar, Accel, Creandum, Lowercarbon, Ribbit, Box Group and strategic angels like Nico Rosberg, the Co-Founder of Solana and GPs behind Meta, Revolut, Spotify, Uber and more.
We’re creating a fully integrated energy company: from developing solar, wind and hydrogen projects to real-time power trading and distributed energy installations. By selling directly to consumers, we cut out the middleman, lower costs and pass on savings to customers.
But we’re not stopping there. We’re also building the Energy Network: a decentralised platform of smart devices to electrify our homes, shifting usage to off-peak hours and helping balance the grid. This network strengthens grid stability - a critical foundation for scaling AI data centers and other energy-intensive industries.
We're now looking to establish a cutting-edge AI team. As an Applied AI Engineer, this position is ideal for someone who possesses the technical expertise of a backend engineer but is specifically interested in applied AI and how it can be used to enhance the energy experience for our customers and our internal operations. You'll be working on a variety of exciting projects, including consumer-focused features like the Energy Co-Pilot and the Speedy Onboarding process (leveraging tools such as VLM/LLM). You will also collaborate across teams to build AI tools that enhance productivity and streamline processes within Fuse.

• Design, develop and deploy AI-powered features that directly impact consumer experiences, including personalised energy recommendations and seamless onboarding via AI models (e.g. using energy bills for quick setup)
• Build and optimise internal AI tools that will make the whole company more productive with a focus on automation and enhancing workflows
• Collaborate with backend engineers and data scientists to integrate AI-driven features into our platforms
• Collaborate with the trading and operations teams to ensure AI models are aligned with real-time market conditions and energy pricing
• Improve AI models to optimise trading strategies by anticipating market shifts based on weather and demand forecasts
• Stay up to date with the latest advancements in applied AI and machine learning and apply them to solve real-world problems within the energy space
• Monitor the performance of AI tools and models, ensuring they are functioning efficiently and effectively