AI Platform Lead

The role

A major financial services organisation is undertaking a three-to-four-year transformation of Commercial Lending, centred on Matrix, its strategic agentic AI platform.

Matrix will provide the foundational capabilities required to support next-generation lending journeys, colleague experiences, intelligent decisioning and broader technology use cases.

Key responsibilities

• Own the Commercial Lending AI platform strategy, target architecture and roadmap.
• Lead the design, engineering and evolution of Matrix and its associated enterprise AI capabilities.
• Establish foundations for agent orchestration, agent lifecycle management and controlled production deployment.
• Lead the integration and serving of LLMs and other models within an enterprise platform.
• Develop reusable services and patterns for tool integration, APIs and retrieval architectures.
• Establish observability, monitoring, evaluation and operational controls for AI systems.
• Drive software and platform engineering standards across automation, testing, reliability and resilience.
• Own the technology lifecycle from architecture and build through implementation, production operations and continuous optimisation.
• Ensure the platform meets relevant security, risk, regulatory, responsible AI and resilience requirements.
• Lead multidisciplinary engineering, platform engineering and architecture teams.
• Translate Commercial Lending priorities into scalable technical capabilities in partnership with business, product, engineering, architecture and risk stakeholders.
• Own delivery sequencing, cost, platform adoption, engineering quality and operational performance.
• Represent the platform strategy at senior and executive governance forums.

Key skills and experience

• Deep, hands-on AI platform architecture and engineering expertise.
• Demonstrable delivery and production operation of enterprise-scale agentic AI platforms.
• Strong cloud-native architecture, distributed systems and modern software engineering experience.
• In-depth understanding of agentic architectures, orchestration frameworks and agent lifecycle management.
• Strong knowledge of LLM ecosystems, model integration and model-serving approaches.
• Practical experience with retrieval architectures, tool integration and enterprise APIs.
• Experience establishing AI observability, evaluation frameworks, governance and operational controls.
• Evidence of creating reusable services, frameworks, standards and engineering patterns for multiple development teams.
• Strong understanding of security, scalability, availability, resilience and production operations.
• Experience leading large multidisciplinary engineering and architecture capabilities.
• Major transformation experience within complex governance environments.
• Strong commercial, financial, risk and executive stakeholder-management capability.

Nice to have

• Experience within financial services or another highly regulated environment.
• Agile and servant leadership experience.