
Fuse Energy
Applied AI Engineer
- Permanent
- Dubai, United Arab Emirates
- Experience 2 - 5 yrs
Job expiry date: 03/06/2026
Job overview
Date posted
19/04/2026
Location
Dubai, United Arab Emirates
Salary
AED 20,000 - 30,000 per month
Compensation
Comprehensive package
Experience
2 - 5 yrs
Seniority
Experienced
Qualification
Bachelors degree
Expiration date
03/06/2026
Job description
The Applied AI Engineer role is part of a renewable energy startup building an integrated energy system combining solar, wind, hydrogen projects, real-time power trading, and distributed energy installations. The role focuses on applied artificial intelligence and machine learning to enhance both consumer energy experiences and internal operational efficiency. The engineer will design, develop, and deploy AI-powered features such as personalised energy recommendations and AI-driven onboarding systems that can process inputs like energy bills using LLM/VLM technologies. The role includes building internal AI tools to improve productivity, automation, and workflow efficiency across the organization. The Applied AI Engineer collaborates with backend engineers and data scientists to integrate AI-driven capabilities into production platforms and works with trading and operations teams to align models with real-time energy market conditions and pricing. The role involves improving AI models to optimise trading strategies by incorporating weather and demand forecasting data, working with large-scale datasets related to energy consumption and supply patterns. The position requires continuous monitoring of AI system performance in production environments and applying advancements in applied AI, machine learning, and NLP to real-world energy industry challenges within a fast-scaling technology environment backed by major global investors.
Required skills
Key responsibilities
- Design and deploy AI-powered consumer-facing features including personalised energy recommendations and AI onboarding systems
- Build and optimise internal AI tools to improve automation, productivity, and workflow efficiency across the company
- Integrate AI and machine learning models into production systems in collaboration with backend engineers and data scientists
- Align AI models with real-time energy trading conditions and pricing in collaboration with trading and operations teams
- Improve machine learning models to optimise trading strategies using weather and demand forecasting data
- Monitor performance of deployed AI systems and ensure operational efficiency and reliability
- Apply advancements in applied AI and machine learning to solve real-world energy sector problems
- Work with large-scale datasets to support forecasting, modelling, and predictive analytics use cases
Experience & skills
- Demonstrate minimum 3 years of engineering experience
- Demonstrate strong backend engineering experience with interest in applied AI or machine learning
- Demonstrate strong programming skills in Python and AI/ML libraries such as TensorFlow or PyTorch
- Demonstrate experience working with large language models (LLMs) or vision language models (VLMs)
- Demonstrate experience deploying AI-driven solutions into production environments
- Demonstrate knowledge of cloud computing and containerisation technologies
- Demonstrate ability to integrate AI/ML models into real-world scalable applications
- Demonstrate experience working with large datasets including forecasting-related data
- Demonstrate problem-solving ability in fast-paced technical environments