Essential Skills/Experience
- Enterprise Architecture experience proven EA leadership translating concepts into production-ready solutions.
- Hands-on AI/ML engineering building, fine-tuning, and deploying ML/DL models (LLMs, RAG, MLOps) in production.
- AI platforms hands-on with AWS (Bedrock, SageMaker, Amazon Q), Azure (Azure AI, ML, OpenAI), and Databricks.
- Engineering and analytics strong Python, TensorFlow/PyTorch, containers, Kubernetes, and CI/CD for hybrid cloud.
- Data modelling and governance conceptual/logical modelling and governance standards in regulated environments.
- Architecture judgement select fit-for-purpose AI architecture per use case, with full-lifecycle understanding.
- Leadership lead a small team of AI architects and help shape enterprise AI strategy and direction.
- Degree in data science, AI engineering, or a related field (or equivalent experience).
Desirable Skills/Experience
- Postgraduate degree in MIS, AI, data science, or a related field.
- Recognised thought leader in applying AI within the enterprise and across the industry.
- Extensive senior AI, data science, data engineering, and AI architecture experience delivering large-scale blueprints.
- Hands-on building AI models, including LLMs and LVMs, across diverse data types.
- Agile AI delivery experience; tools for metadata cataloguing, data modelling, and enterprise architecture.
- Experience in the pharmaceutical AI industry.
- Ability to simplify the enterprise landscape and reduce technology debt.
