Enterprise Architecture Lead

We're excited to be partnering with a leading institution in the UAE that is building a digital-first, AI-enabled financial services organisation from the ground up. This is a unique opportunity to join at an early stage and help shape the technology, data, and AI foundations of a business with significant institutional backing and long-term ambition. As Enterprise Architecture Lead, you will be responsible for defining and governing the enterprise technology landscape, integration architecture, AI architecture standards, and technology strategy. Working closely with Technology, Data & AI, Solution Architecture, and delivery partners, you'll play a key role in establishing the architectural foundations that enable a secure, scalable, and AI-native financial institution from day one.Key Responsibilities:• Own and maintain technology landscape, including business capability models, application portfolios, platform maps, target-state architecture, and transition roadmaps.• Design the architecture that enables AI agents to operate as governed members of the organisation, including agent orchestration, non-human identity, permissioning, and human-in-the-loop supervision.• Architect the organisation's intelligence layer, including AI gateways, model registries, agent registries, evaluation frameworks, guardrails, and feedback mechanisms.• Define and govern enterprise integration architecture, including API standards, event-driven architecture, streaming platforms, schema governance, and agent-facing protocols such as MCP.• Build and maintain machine-readable enterprise architecture models that support automated governance, architecture conformance, and AI-assisted decision-making.• Develop reference architectures for resilience, disaster recovery, observability, identity management, auditability, and enterprise data movement.• Lead technology selection, architecture governance, vendor evaluations, and challenge system integrator designs to ensure alignment with enterprise standards.• Establish and enforce enterprise architecture standards across a complex multi-vendor ecosystem while managing deviations and remediation activities.• Support regulatory reviews, licensing activities, audits, operational resilience requirements, and AI governance initiatives through robust architectural controls and evidence-based documentation.Required Experience: 10+ years in enterprise architecture within banking or financial services, including hands-on architectural leadership of a greenfield build or enterprise-scale transformation — operating at estate level, above individual solution design. Demonstrable experience architecting AI/ML and agentic systems in production — platform patterns for model deployment, orchestration, evaluation, and governance — beyond proof-of-concept work. Track record designing integration architectures at bank scale — event-driven and API-based — and holding multiple vendors and system integrators to common standards. Deep familiarity with modern cloud architecture (Azure preferred), including hybrid and private-cloud target states and data residency-constrained design. Direct experience in a regulated environment: architecture support for licensing, audits, model risk reviews, and operational resilience expectations. A record of landing complex, contested technology decisions with executive stakeholders in politically demanding environments. Ability to work in a fast paced start up environment, building and implementing an enterprise tech road map.Excellent stake holder management and negotiating skills.Technical Expertise: AI and agentic architecture: LLM gateways, model serving and registries, agent orchestration frameworks, tool-use patterns, evaluation and guardrail tooling, LLMOps. Enterprise architecture practice: capability mapping, application portfolio management, and target/transition-state design — expressed as machine-readable models rather than framework documentation. Integration technologies: event streaming platforms (Kafka or equivalent), API management, schema registries, OpenAPI/AsyncAPI/CloudEvents, agent integration protocols (MCP and comparable), and non-human identity and workload authentication. Cloud and infrastructure architecture: Azure landing zones, Kubernetes-based platforms, resilience and DR patterns, and infrastructure-as-code operating models. Responsible AI and model risk: explainability, decision audit trails, containment and permissioning models, and alignment with regulatory expectations for AI in banking. Qualifications: Bachelor's degree in Computer Science, Information Systems, or a related discipline; relevant postgraduate qualification an advantage. Cloud architecture certification (e.g. Azure Solutions Architect Expert) an advantage.