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The Director, Tech & Platforms serves as the technical co-leader of the AI Center of Excellence, owning the architecture, platforms, and engineering foundations that enable AI at scale across Zain Group. This director-level role engages as a peer with Group technology directors (CTO, IT, Data, Security) and OpCo AI Office Heads to set technical strategy, enforce architecture standards, and ensure production-ready AI systems. The Director defines Zain's AI reference architecture, leads platform selection and vendor management, establishes engineering practices, and builds internal technical capability. This role requires deep AI/ML platform expertise, enterprise architecture leadership, and the executive presence to influence senior stakeholders across a federated organization.
Define and maintain Group AI reference architecture for GenAI, Agentic AI, ML, and intelligent automation
Own AI platform strategy and service catalog including LLM platforms, orchestration, MLOps, and data platforms
Lead platform evaluation, vendor selection, commercial negotiations, and implementation oversight
Establish and enforce technical standards for AI delivery including coding practices, deployment patterns, and monitoring
Chair Group AI Architecture Review Board with OpCo CTO/IT directors to drive alignment and manage exceptions
Enable delivery teams with proven engineering practices, tooling, accelerators, and technical problem-solving
Define and oversee AI production operations including SLAs, monitoring, incident management, and continuous improvement
Partner with Group CTO, IT, Data, and Security directors on platform integration, infrastructure, and compliance
Serve as technical peer to 6 OpCo AI Office Heads for architecture guidance and cross-OpCo alignment
Build and develop high-performing technical team of architects and engineers
Manage structured knowledge transfer from Strategy& and delivery partners to build internal capability
KPIs can include but are not limited to:
Platform adoption: percentage of OpCos using shared Group AI platforms
Time-to-production: average time from use case approval to production deployment
Architecture compliance: percentage of initiatives aligned to reference architecture
System reliability: uptime and performance of AI platforms meeting defined SLAs
Internal capability: percentage of use cases delivered by internal team vs. external vendors
Educational Qualifications: Bachelor's degree in Computer Science, Engineering, or related technical field. Master's degree in AI/ML, Data Science, or Computer Science preferred.
Experience: 15+ years in technology leadership roles with progression from engineering to architecture to leadership. Experience building and operating AI/ML platforms at enterprise scale, designing reference architectures, and leading technical teams in federated organizations. Telecom or complex regulated industry experience highly valuable.
Knowledge: Deep expertise in GenAI/Agentic AI, MLOps/LLMOps, cloud platforms (AWS/Azure/GCP), data platforms, and enterprise integration. Strong understanding of architecture governance, platform operations, and vendor management. Experience with telecom BSS/OSS systems advantageous.
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