Applied AI Engineer

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. We’re building a cutting-edge AI team, and this role is for an engineer who wants to apply AI to real problems in energy. As an Applied AI Engineer, you’ll help build our Product Factory: an agentic pipeline that takes software from requirements and design through code review, deployment and monitoring, with human review where the risk calls for it. You’ll also ship customer-facing features using VLMs and LLMs, and build AI tools and agents that make teams across Fuse more productive, from customer support to warehouses and back office. This is an applied engineering role, not pure research: you’ll own what you build, from spec to production. Responsibilities - Ship AI features for customers, such as personalised energy recommendations and onboarding from an energy bill. - Build LLM applications and agents for support, engineering, warehouse and back-office teams, including multi-agent systems and durable workflows (e.g. Temporal). - Build the engineering around them: cloud infrastructure, integrations, and access control so users and agents only reach what they should. - Own evaluation: datasets, golden answers, human and LLM judges, A/B tests. Know whether a change genuinely helped. - Choose models by performance, latency and cost, and revisit as models improve. - Work with trading, operations and backend teams so models reflect real-time market conditions, energy pricing and demand and weather forecasts. - Monitor AI systems in production and keep them reliable. Benefits - Competitive salary and eligibility for equity - Biannual bonus scheme - Fully expensed tech to match your needs - Private health insurance - Breakfast and dinner allowance for office-based employees As we hire globally, benefits may vary by location.

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 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 real-world problems in the energy space. Monitor the performance of AI tools and models, ensuring they run efficiently and effectively.