REQUIRED SKILLS & EXPERIENCE

• Proven leadership in AI, with a background in computer science, machine learning, data science or a related STEM field (degree or equivalent experience).
• Hands-on experience developing and deploying production-grade ML models, including advanced RAG (retrieval-augmented generation) systems.
• Deep expertise in Generative AI, LLMs, NLP, and Knowledge Graphs-with a track record of translating complex models into real-world business solutions.
• Strong engineering fundamentals, including DevOps, CI/CD, and secure ML/AI pipelines (DevSecOps).
• Highly proficient in Python, SQL, and key AI/ML frameworks (e.g., PyTorch, TensorFlow).
• Ability to mitigate model hallucination, optimise performance, and lead governance around AI risk and ethical deployment.

• Lead the identification of opportunities and risks in a fast-evolving competitive landscape, using AI/ML to deliver measurable business value & growth.
• Understand and maintain a RADAR of technologies, in order to understand the risk and reward profile of selecting a technology to capitalise on an opportunity or mitigate a risk
• Own the lifecycle of AI initiatives; from vision through to design, delivery, and optimisation in high-performance, high-volume environments.
• Build evidence-based business cases to influence senior stakeholders and drive organisation-wide adoption.
• Empower delivery teams with the tools, capabilities, and insights needed to embed AI at scale.