Buildings account for 34% of global CO₂ emissions. ZUNO is building systems to rapidly and efficiently decarbonise buildings at scale - accelerating the transition to a net zero future.
We're looking for an AI Engineer to own and lead the development of AI systems across ZUNO - from backend automation that drives operational efficiency to intelligent features that enhance the customer experience. You'll be responsible for building new capabilities from the ground up while also optimising and scaling the high-impact AI workflows we already have in place.
This is an execution role, not a research role. You'll take commercially critical use cases and ship production-ready AI systems that can handle massive volumes, integrate seamlessly into our stack, and deliver measurable impact.
What the job involves:
- Own AI at ZUNO - Take full responsibility for designing, improving, and deploying AI systems across the business
- Optimise existing workflows - Refine and scale our current AI tools to deliver even greater efficiency, accuracy, and reliability
- Backend automation - Build robust systems that streamline operations and enable us to scale with minimal friction
- Enhance customer experience - Develop AI-driven features that improve relevance, speed, and personalisation for customers
- End-to-end delivery - From concept to production, including data sourcing, model integration, fine-tuning, and performance monitoring
- Experiment & innovate - Rapidly test new capabilities and apply them to high-value opportunities
- Commercial focus - Build solutions that directly drive growth, efficiency, and measurable climate impact
Requirements
Must haves:
- Exceptional ambition - Proven top-tier performance in academic, technical, or personal projects
- Proven delivery track record - You've built and deployed AI systems from prototype to production at scale, with clear evidence of business impact
- Technical fluency - Strong in Python and SQL, with experience designing and integrating APIs. Comfortable working with cloud platforms and applying MLOps best practices to deploy, monitor, and scale AI models in production
- Clear commercial thinking - You understand the "why" behind the "how" and can design for ROI
- Builder mindset - Self-starting, hands-on, and able to create new systems from scratch
- Adaptability - Comfortable switching between backend automation, data engineering, and model deployment
Nice to haves:
- You have energy or construction experience - Knowledge of solar, heat pumps, or other low carbon energy systems
Benefits
- Free On-site Gym
- Regular Company Socials
- 25 Days Holiday (excl. bank holidays)
- Pension Plan
- Travel Insurance
- Free Wellness Subscriptions (10 ClassPass credits per month, Headspace, Freeletics, Sleep Cycle, Uber One, Financial Times, The Athletic and Chess.com)
Our culture:
- Move fast - High energy, high performance, high standards
- No passengers - Everyone pulls their weight
- Founders' mentality - Everyone thinks like an owner
- Mission obsessed - We're not here to build another startup. We're here to fix the planet
