Senior Manager – AI Control Tower

To lead the engineering and operational management of the ADCB AI estate by providing accountable service ownership, consolidated performance visibility, and capacity management. Own the development and scaling of shared AI access, connectivity and integration with models, agents, and enterprise services. Drive standardisation, intelligent automation, and continuous optimisation across the AI estate, enabling secure, efficient, and resilient adoption at enterprise scale.

Own and evolve the technical strategy, service architecture and roadmap for AI access, integration, and operational capabilities. Define reusable service patterns, engineering standards and ownership boundaries across models, agents, APIs, and shared enterprise services. Lead the design and operation of API and LLM gateways, MCP services and enterprise integrations. Define routing, authentication, access policies, throttling, versioning, and reusable integration patterns. Establish repeatable onboarding, configuration, release and retirement processes for models, agents, and shared services.

Maintain dependency inventories, compatibility checks, evaluation evidence, and tested rollback procedures. Define telemetry and tracing standards across model calls, agent execution, and tool interactions. Correlate availability, latency, quality and consumption signals to diagnose degradation and prioritise engineering improvements. Set service objectives and drive capacity, load, and resilience testing. Lead technical incident resolution, root-cause analysis, and recovery exercises; automate recurring remediation within agreed operational controls.

Establish usage metering, cost attribution and demand forecasts across services and consumers. Optimise quotas, committed capacity, routing, and caching against cost per successful task, performance, and quality targets. Establish engineering standards and automated controls that support responsible AI adoption. Shape the evolution of Control Tower capabilities to meet emerging model, agent, and enterprise service needs. Lead major operational coordination, incident management, action tracking, disaster‑recovery readiness, and business‑continuity evidence, while routing security events to the designated Cybersecurity function.

Manage operational and technical performance of cloud, model, platform and resource partners against agreed deliverables, service levels, evidence requirements, and knowledge‑transfer commitments. Maintain first‑line operational controls, evidence and remediation tracking for change, security, data protection, architecture, and audit requirements; escalate risk acceptance and independent assurance decisions to authorised functions. Provide technical leadership to AI platform, operations, and reliability engineers, ensuring architectural alignment, engineering quality, and resilient delivery across shared AI services.

Mentor engineers in AI‑assisted development, lifecycle automation, observability, and performance optimisation, building capability to support advanced models and agent systems. Drive technical reviews and continuous improvement, introducing reusable patterns, engineering accelerators and automated controls that strengthen platform reliability, cost efficiency, and developer experience. Manage self and team in line with ADCB's people management policies, procedures, processes, and practices to ensure adherence and to maximise own and employee contribution to business performance.

Organise and supervise the activities and work of the team to ensure that targets and objectives are achieved and the business plan is delivered in line with the required policies, processes, procedures, and systems Implement approved…