· Work with product owners, engineering teams, and industry partners throughout the product development lifecycle from concept, design, prototyping, acceptance testing, data curation, delivery, operationalisation, industry proliferation, to product end-of-life
Infrastructure & Engineering Excellence: Manage infrastructure and CI/CD pipelines while ensuring scalability, performance, security, and high code quality through best practices and governance.
• Collaborate with Data Engineers and IT Subject Matter Experts (SMEs) to understand health data sources and define architecture patterns that prepare, govern and optimize data for Generative AI-based solutions.
Experience of working in a multicultural, multidisciplinary and multi-ethnic environment, contributing to the development of mutual understanding, trust and tolerance
Own client delivery governance: Run SteerCos, write sharp status updates that executives can read in 5 minutes, and flag risks, dependencies and decisions early in business terms.
Liaise with suppliers and delivery personnel to verify shipment details, resolve discrepancies, and communicate any issues or concerns about the condition of goods received.
Define and implement the "Definition of Done" for AI using quantitative evaluation. Use evaluation tools (e.g. DeepEval) to score models on Faithfulness and Relevancy. Use these metrics to validate model upgrades and cost-optimisation experiments
Conduct research and stay up to date with the latest advancements in AI and machine learning, integrating new technologies and methodologies into the team’s workflows.