Sr AI Platform & Delivery Lead

Key responsibilities Deployment & platform  Own the AI deployment pipeline (Dev → UAT → Production) and the sandbox environment, ensuring a clear, governed, repeatable path to production.  Operate and govern the on-prem / sovereign AI platform (Kubernetes, containerisation, GPU orchestration) — configuring and managing it, including partner-provided components.  Establish a reusable “golden path” deployment pattern so each successive use case ships faster than the last. Vendor & delivery management  Act as the technical counterpart to AI vendors and the implementation partner — review their architectures, challenge unrealistic timelines, and hold them to delivery commitments.  Validate that vendor-delivered solutions (container images, models, integrations) meet the bank’s security and residency requirements before deployment.  Set the technical standards every vendor must deliver to, so solutions arrive in a form our environment can actually run. Security & integration  Work directly with Information Security (ISO) to enable and run container image vulnerability and malware scanning (IVA/MSB) for AI workloads.  Work with IT Infrastructure to provision, scale and govern compute for AI workloads.  Own the integration of third-party AI products into the bank’s systems and data. MLOps & governance  Stand up and run model registry, versioning, monitoring and drift detection — so models stay accountable after go-live, not just at delivery.  Ensure all AI in production is observable, auditable and aligned to CBO and risk expectations. Must-have experience  10+ years in platform / DevOps / MLOps or AI engineering, with a track record of putting solutions into live production  Hands-on Kubernetes, Docker / containerisation, and container security in production.  On-premise / sovereign /in-region deployment experience — not cloud-only. Data residency is non-negotiable.  Proven management of software / AI vendors and integration ofthird-party systems — ideally in a bank, telco or government.  Able to read a vendor’s architecture and identify what will not work — strong enough technically not to be bluffed.  Experienced in managing AI Projects, as a project manager