Enterprise Architect

Roles and Responsibilities :

• 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.