Head of Engineering (AI)

At Fuse, we are building a fully integrated energy company, from developing solar, wind, and hydrogen to power trading and distributed energy installations. We sell directly to energy consumers, cutting out the middleman to reduce costs and pass on savings to customers. We are also building the Energy Network: a decentralized network of smart devices where users get rewarded in Energy Dollars for electrifying their homes, shifting usage to off-peak hours, and helping balance the grid. The energy network helps the grid achieve energy stability, a crucial requirement for the growth of AI data centres and energy-intensive industries.

We have raised $90M from top-tier investors including Multicoin, Balderton, Lakestar, Accel, Creandum, Lowercarbon, Ribbit, Box Group, and strategic angels like Nico Rosberg, co-founder of Solana, and GPs behind Meta, Revolut, Spotify, Uber, and more.

Role Overview

As the Head of Engineering (AI) at Fuse Energy, you will lead the development and integration of AI across our platform—from intelligent forecasting models and optimization algorithms to personalized customer experiences and internal automation. This role is both strategic and hands-on. You will own the engineering strategy for how AI is built, deployed, and scaled across our stack, partnering closely with data science, product, and platform teams.

What You’ll Do

• Own the AI engineering roadmap and lead the development of AI-first features
• Productionize ML models, ensuring scalability, performance, and observability
• Design the infrastructure for deploying and maintaining ML systems in production (e.g., MLOps, CI/CD for ML, model versioning)
• Build systems that integrate AI into key parts of our stack, such as:

• Forecasting customer demand and renewable generation
• Dynamic pricing and energy trading algorithms
• Intelligent alerts and personalized customer features

Requirements

• Strong software engineering background with 5+ years of experience, including at least 2 years leading AI/ML engineering teams
• Deep experience deploying ML models into production environments
• Proficiency in designing scalable data pipelines and real-time inference systems
• Understanding of modern ML tooling and frameworks (e.g., PyTorch, TensorFlow, MLflow, AWS SageMaker)
• Strong cross-functional collaboration skills, particularly with data science and product teams
• Clear communication and an ability to prioritise for both experimentation and reliability

Bonus

• Familiarity with optimization, time series modelling, or forecasting
• Experience with large language models (LLMs), RAG, or generative AI in production
• Background in MLOps or AI infrastructure at scale

Competitive salary and a stock options sign-on bonus. Biannual bonus scheme. Fully expensed tech to match your needs! Paid annual leave. Breakfast and dinner for office-based employees.