Applied AI Engineer

About the role

Fuse Energy is building a next-generation renewable energy business with the goal of unlocking a terawatt of clean energy as quickly as possible. The company blends first-principles thinking with advanced technology to reshape how energy is produced, traded, and delivered.

The business has secured $170M in funding from investors including Multicoin, Balderton, Lakestar, Accel, Creandum, Lowercarbon, Ribbit, Box Group, and strategic backers such as Nico Rosberg, the Co-Founder of Solana, and partners associated with Meta, Revolut, Spotify, Uber, and more.

Its platform spans the full energy value chain: developing solar, wind, and hydrogen projects; enabling real-time power trading; and supporting distributed energy installations. By selling directly to customers, the company aims to reduce intermediary costs and pass savings on to end users.

Fuse Energy is also developing the Energy Network, a decentralised ecosystem of smart devices designed to electrify homes, move usage into off-peak periods, and support grid balancing. This infrastructure is intended to strengthen grid stability, which is increasingly important for AI data centres and other power-intensive industries.

The company is now forming a dedicated AI team and is hiring an Applied AI Engineer to help build practical AI products for customers and internal teams. This role is suited to someone with backend engineering depth who is especially motivated by applied AI and its use in improving the energy experience. Projects may include customer-facing tools such as the Energy Co-Pilot and a faster onboarding flow using VLMs/LLMs, along with internal tools that improve productivity and streamline operations.

What you'll do

• Develop and launch AI-enabled product features that improve the customer experience, such as tailored energy guidance and faster onboarding using AI models, including workflows that analyse energy bills.
• Create and refine internal AI tools that automate work and help teams operate more efficiently.
• Work closely with backend engineers and data scientists to embed AI capabilities into core platforms.
• Partner with trading and operations teams so AI outputs reflect live market dynamics and energy pricing.
• Enhance models that support trading decisions by forecasting possible market movement using weather and demand signals.
• Keep track of new developments in applied AI and machine learning, then translate relevant ideas into energy-sector use cases.
• Measure and maintain the performance of AI tools and models to ensure they remain effective and efficient.

What we're looking for

• At least 3 years of engineering experience.
• Background as a backend engineer with hands-on involvement in applied AI or machine learning.
• Strong Python skills, or equivalent, plus familiarity with ML frameworks such as TensorFlow or PyTorch.
• Experience working with large language models and vision-language models, including production deployment of AI systems.
• Good knowledge of cloud platforms, containerisation, and scalable AI application design.
• Ability to integrate machine learning models into practical products with attention to usability and performance.
• Strong analytical and problem-solving ability, with a bias toward building workable solutions in a fast-moving environment.
• Experience handling large datasets, especially for supply and demand forecasting.

Nice to have

• Interest in or experience with energy markets and trading strategies.
• Understanding of weather forecasting, energy demand trends, and production modelling.
• Exposure to natural language processing or similar AI specialties.

Benefits

• Competitive compensation plus an equity sign-on bonus.
• Biannual bonus programme.
• Fully funded technology setup matched to your needs.
• Paid annual leave.
• Breakfast and dinner support for employees working from the office.

Additional information

This is a full-time onsite position based in Dubai, Dubai, United Arab Emirates.