AI Engineering Lead

Join usasaAIEngineering Lead * In this key role,you’lllead the engineering of AI and machine learning(ML)capabilities for the Economic Crime Hub, translating decision strategies into scalable, production-grade solutions * We’lllook to you to own the end-to-end lifecycle of AI andMLmodels, from development and deployment through to monitoring, optimisation, and ongoing performance management * This is an opportunity to make an impact by ensuring AI andMLsolutionsoperatereliablyandsafelywithin governed,compliant environments, while meeting business, risk, and regulatory requirements Whatyou'lldo AsaAI Engineering Lead,you'lllead the design, build, and deployment of ML models and AI systems into production environments.You'lltranslate decision strategies and analytical requirements into production-grade solutions, designing reusable pipelines and frameworks that support efficient delivery while ensuring reliable, high-quality outcomes that advance the Economic Crime Hub'sobjectives. Moreover,you’llestablishand evolve ML engineering standards, tooling, and best practices across the Hub, while partnering closely with Analytics, Product, and Technology teams to deliver end-to-end decisioning capabilities.You’llalsodrive the development of AI platformarchitectureand infrastructure to support the secure and efficient deployment of AI solutions, while providing technical leadership across ML engineering and AI disciplines to drive innovation, strengthen capability, and promote the adoption of effective solutions. In Addition,you’llbe * Owning the end-to-end model lifecycle, including deployment, monitoring, optimisation, retraining, and decommissioning * Overseeing model performance in production, including accuracy, stability, drift, and real-world effectiveness * Embedding controls, monitoring, and validation within AI andMLsolutions to ensure safe and compliant decision-making * Ensuring the technical integrity, resilience, and scalability of AI systems in alignment with enterprise architecture standards * Ensuring models are explainable, auditable, and compliant with governance requirements, working in partnership with Model Risk and Assurance * Enabling the automation of decision-making through AI and reducing reliance on manual intervention * Building and leading a high-performingMLengineering capability, including hiring, development, and technical progression of team members The skillsyou'llneed We’relooking for someone with extensive experience designing, building, and deploying production-grade AI andMLsolutions,supported bya strong understanding of ML engineering,Machine Learning Operations(MLOps), and model lifecyclemanagement.You’llbring the technicalexpertiseto translate analytical models and decision strategies into robust, operational systems that deliver business value within regulated environments. To succeed in this role, youmustalsohave aproventrack recordof developing AI platformsand deployment capabilities that support the secure, reliable, and efficient delivery of AI solutions. Equally important is the ability to provide technical leadership, collaborate across multidisciplinary teams, and drive innovation whilemaintainingstrong governance and risk management practices. In Addition,you’llneedtodemonstrate * Extensive experience designing and delivering production-gradeMLand AI systems * Deepexpertisein ML engineering and model lifecycle management, including deployment, monitoring, optimisation, and ongoing performance management * Strong knowledge ofMLOpspractices, including CI/CD, pipeline orchestration, automation, and production model management * Proven ability to translate analytical models and decision strategies into robust, operational decisioning systems * Experience developing AI platforms, scalable architectures, and reusable engineering components that enable efficient AI solution delivery * Experience working in regulated environments, with a strong understanding of governance, explainability, model risk, and compliance requirements * Proven leadership and stakeholder management skills, with the ability to collaborate across Analytics, Product, and Technology teams while building and developing high-performing technical teams