This organisation is a well-established leader in the utilities sector, delivering critical services to a large and growing customer base. With a strong focus on innovation, sustainability, and future-ready technology, they are investing heavily in data, AI, and advanced analytics. Their technology function is undergoing a major uplift, with AI positioned as a key driver of smarter decision-making, operational efficiency, and long-term value creation. You’ll be joining a business where AI is not just experimental—it’s becoming embedded across the enterprise. About the Role
This is a senior, hands-on leadership role responsible for building and scaling enterprise AI capability. As Lead AI Engineer, you’ll design, develop, and deploy AI and machine learning solutions that deliver tangible business outcomes across complex operational environments. You’ll work closely with data leaders, architects, and business stakeholders to identify opportunities and bring high-impact AI use cases to life—from predictive models through to cutting-edge generative AI solutions. Key responsibilities
Leading end-to-end AI/ML solution design, development, and deployment Driving innovation across NLP, LLMs, and advanced ML techniques Establishing and scaling MLOps practices (CI/CD, monitoring, lifecycle management) Building on modern cloud and data platforms (Azure, Databricks) Embedding AI into enterprise systems to improve efficiency and decision-making Championing governance, best practice, and responsible AI frameworks Mentoring engineers and leading cross-functional delivery teams This role offers a strong mix of strategy and hands-on engineering, with real influence over how AI is adopted across the organisation. About You
You’re an experienced AI/ML engineer with a strong track record of delivering production-ready solutions at scale. You’re comfortable operating across both technical and business domains and enjoy turning complex ideas into practical outcomes. What you’ll bring
Strong background in software or data engineering (Python preferred) Deep experience with ML frameworks (TensorFlow, PyTorch, scikit-learn) Solid MLOps capability, including model deployment and monitoring Experience with cloud platforms (Azure preferred) and Databricks ecosystem Exposure to generative AI, LLMs, and modern AI frameworks (e.g. LangChain) Proven ability to deliver AI solutions that drive measurable business value Strong stakeholder engagement and leadership experience
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