AI/Agentic AI Lead

Al Gurg Group; Dubai; On-site; AED 1,400,000 - 2,100,000; Full time

Job summary

Al Gurg Group seeks a senior AI leader to own and evolve the Group AI and Agentic AI roadmap, aligning with the GCIO strategy and commercial priorities across operating companies.

You will identify and document business use cases, prioritize initiatives by value and feasibility, and build business cases and benefit tracking to guide investment decisions.

Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, Data Science, Information Technology, or a related discipline.
• Master’s degree in Artificial Intelligence, Data Science, Computer Science, or an MBA with a technology focus is strongly preferred.

Responsibilities

• Own and evolve the Group AI and Agentic AI roadmap aligned with GCIO strategy and commercial priorities.
• Identify, qualify, and document candidate business use cases across finance, procurement, supply chain, sales, service and human capital.
• Prioritise AI initiatives using a structured assessment of business value, technical feasibility, risk, data readiness; maintain portfolio view for executive review.
• Develop business cases, cost models, and benefit tracking to ensure evidence-based AI investments.
• Lead vendor evaluation and solution selection; manage governance across AI portfolio; ensure implementation readiness and post-go-live benefit review.
• Translate technical capability into plain business language for boards and management; build AI literacy across the Group.

Skills

Agentic AI frameworks

GenAI platforms

AI governance

Executive communication

Commercial acumen

Security & data governance

Team leadership

Education

Bachelor’s degree in CS/Engineering/Data Science/IT

Master’s in AI/Data Science/CS or MBA with tech focus

Job description

Strategy Roadmap Portfolio Ownership Own and continuously evolve the Group AI and Agentic AI roadmap aligning it to the GCIO s technology strategy and to the commercial priorities of each operating company Work with the GCIO business leaders and functional heads to identify qualify and document candidate business use cases across finance procurement supply chain sales service and human capital Prioritise AI initiatives using a structured assessment of business value technical feasibility risk exposure and data readiness and maintain a transparent portfolio view for executive review Develop business cases cost models and benefit-tracking mechanisms so that AI investment decisions are evidence-based and outcomes are measurable post-deployment Maintain an informed position on the AI and Agentic AI market advising leadership on emerging capabilities obsolescence risk and the Group s competitive positioning Agentic AI Solution Design Architecture Design Agentic AI solutions and workflows defining agent roles task decomposition orchestration patterns memory and context strategies and success criteria Define how agents interact with enterprise systems and knowledge sources ERP CRM HRMS procurement platforms the data lake document repositories email and internal and external APIs Build solution blueprints covering multi-agent workflows human-in-the-loop approval points escalation rules fallback behaviour and complete audit trails for every automated action Ensure solution architecture is scalable secure reusable and fully aligned with enterprise IT standards reference architectures and integration patterns Establish reusable components prompt libraries evaluation harnesses and design patterns that reduce the cost and lead time of each subsequent AI initiative Vendor Evaluation Delivery Governance Lead vendor evaluation and solution selection defining requirements running structured proofs of concept and comparing platforms on capability cost security posture and roadmap credibility Negotiate scope and deliverables with implementation partners in coordination with Procurement and Legal and hold partners accountable to agreed quality and timeline commitments Provide implementation governance across the AI portfolio stage gates architecture review testing standards deployment readiness and post-go-live benefit review Manage AI programme budgets consumption costs and licensing ensuring predictable and optimised spend as workloads move from pilot to production Governance Risk Responsible AI Define and enforce the Group s Responsible AI framework covering permitted use cases data classification model selection human oversight and prohibited applications Work with Cybersecurity Legal Compliance and Internal Audit to ensure AI solutions meet UAE data protection requirements and internal control expectations Establish monitoring for model drift hallucination risk bias and unintended agent behaviour with clear thresholds for intervention or rollback Maintain documentation and audit evidence sufficient to explain any automated decision to internal audit external auditors or a regulator Team Leadership Business Enablement Lead and develop a multidisciplinary team of AI engineers agent developers and data specialists setting technical direction and quality standards Work closely with enterprise application emerging technology infrastructure and cybersecurity teams to ensure AI capability is embedded rather than isolated Build AI literacy across the Group through structured enablement communities of practice and clear guidance on safe and effective everyday use Act as the Group s internal authority on AI translating technical capability into plain commercial language for boards executives and operating company management Bachelor’s degree in Computer Science, Software Engineering, Data Science, Information Technology, or a related discipline. - Master’s degree in Artificial Intelligence, Data Science, Computer Science, or an MBA with a technology focus is strongly preferred.

Professional Certifications

• Professional certification in a major AI or cloud platform (Microsoft Azure AI Engineer / Solutions Architect, AWS Machine Learning or Solutions Architect, Google Cloud Professional ML Engineer, or equivalent).
• Enterprise or solution architecture certification such as TOGAF is advantageous.
• Project or programme management certification (PMP, PRINCE2, or Agile/SAFe) is advantageous.
• Credentials in AI governance, risk, or data privacy (for example ISO/IEC 42001 or CIPP) is an asset.

Experience

• 8-10 years of experience in data, automation, AI, Generative AI, analytics, or digital transformation initiatives.
• Demonstrated ownership of an AI or automation roadmap at group, enterprise, or multi-entity level.
• Proven experience designing and deploying Generative AI or Agentic AI solutions into production, not solely proofs of concept.
• Track record of leading vendor evaluation, solution selection, and third-party implementation governance.
• Experience working within or alongside enterprise application, infrastructure, and cybersecurity functions in a complex, multi-entity organisation.
• Experience leading technical teams and influencing senior business stakeholders; regional or UAE experience is an advantage.

Key Skills & Attributes

• Strong command of Agentic AI frameworks and enterprise GenAI platforms, with the depth to challenge vendor claims credibly.
• Ability to translate ambiguous business problems into prioritised, technically feasible AI solutions.
• Excellent written and verbal communication, including executive-level presentation and business case writing.
• Sound commercial judgement on build-versus-buy, licensing, and consumption cost.
• Rigorous approach to security, data governance, and auditability of automated decisions.
• Collaborative leadership style with the resilience to drive change across independently managed operating companies.