Lead AI Engineer

- A minimum of a 2.1 degree in Computer Science, AI, Data Science, Statistics, or in a similar quantitative field. - Demonstrable experience of deploying modern AI/ML solutions into production, including prompt engineering, retrieval-augmented generation (RAG), model evaluation, and monitoring using metrics (e.g. precision, recall, NDCG and drift detection). - Strong Python skills with a grounding in software engineering best practices (CI/CD, testing, code reviews etc). - Experience developing solutions at scale on cloud platforms (Azure & AWS), containerisation and orchestration tools such as Kubernetes and Docker. - Expertise in data engineering for AI: handling large-scale, unstructured, and multimodal data. - Understanding of responsible AI principles, model interpretability, and ethical considerations. - Strong interpersonal skills with the ability to lead client projects and establish requirements in non-technical language. - Experience in managing, coaching, and developing junior members of a team and wider community. - (Desirable) Demonstrable experience with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g. GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). - (Desirable) Experience with data storage for AI, vector databases, semantic search, and knowledge graphs. - (Desirable) Contributions to open-source AI projects or research publications. - (Desirable) Familiarity with AI security, privacy, and compliance standards e.g. ISO42001.