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AI Advisory

U X E SECURITY SOLUTIONS L.L.C
Dubai, UAE
fulltime
Mid-Senior
Today
Strategic PlanningMarket AnalysisFinancial ModelingBusiness DevelopmentStakeholder ManagementConsulting
Free

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Strategic PlanningMarket AnalysisFinancial Modeling
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Job Structure

Direct Reporting to

Head of AI / Chief Technology Officer / Chief Digital Officer

Summary

The AI Advisory Manager serves as the primary technical AI strategy advisor within the AI Center of Excellence.

The role translates complex AI landscape developments into actionable roadmaps and architectural recommendations, advises senior management on AI opportunities and risks, and manages cross-functional advisory engagements across the CoE.

Job Description

A management-level role within the AI Leadership & Governance department.

The role bridges technical AI expertise with organisational strategy — advising internal CoE teams, leadership stakeholders, and vendor partners on the selection, design, and governance of AI systems.

Accountable for maintaining technical excellence across the CoE and ensuring all AI initiatives align with organisational objectives, regulatory requirements, and international best practices.

Job Responsibilities And Accountabilities

  • Develop and maintain the AI strategy and technical roadmap aligned with organisational objectives
  • Advise senior management on AI opportunities, risks, and emerging technology trends
  • Identify business processes suitable for AI enhancement and lead use-case development
  • Lead AI-related projects from concept through to implementation and post-deployment review
  • Evaluate AI tools, platforms, and vendors to ensure alignment with technical and business requirements
  • Collaborate with internal departments to assess AI requirements, define solutions, and support adoption
  • Establish and enforce AI governance, ethics, and compliance standards across all AI initiatives
  • Provide architectural guidance on AI system design, scalability, security, and integration
  • Monitor performance and effectiveness of deployed AI systems and drive continuous improvement
  • Deliver training, guidance, and AI literacy sessions to stakeholders across the organisation
  • Stay current on industry developments, regulatory changes, and advancements in AI
  • Prepare technical reports, presentations, and advisory papers for leadership

Experience Required

  • Minimum 8–10 years of progressive experience in technology, AI, digital transformation, or data analytics
  • Proven experience leading AI initiatives and strategic advisory projects in complex environments
  • At least 3 years in a senior advisory, architect, or management capacity
  • Experience advising executive or C-suite stakeholders on AI strategy and technology decisions
  • Exposure to regulated or government environments preferred

Qualifications

  • Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, or a related field (required)
  • Master's degree in AI, Data Science, or related field (preferred)
  • Relevant certifications preferred: Google Professional ML Engineer, AWS ML Specialty, Azure AI Engineer Associate, TOGAF, or PMP

Technical Skills Required

  • Large Language Models (LLMs) & Generative AI — GPT-4, Claude, Gemini
  • Agentic AI systems & multi-agent frameworks — LangChain, AutoGen, CrewAI
  • Retrieval-Augmented Generation (RAG) architectures & vector databases
  • Cloud AI platforms — Azure OpenAI Service, AWS Bedrock, Google Vertex AI
  • Machine learning frameworks — PyTorch, TensorFlow, Scikit-learn
  • MLOps — model lifecycle management, deployment, monitoring, and observability
  • Data architecture — pipelines, warehousing, knowledge graphs
  • AI governance frameworks — responsible AI, ethics, risk assessment methodologies
  • API design, microservices architecture, and system integration concepts

Soft Skills

  • Strategic thinking — connects technical AI capability to organisational vision and long-term outcomes
  • Executive communication — confident presenting to senior leadership with clarity and authority
  • Stakeholder management — builds trust-based relationships with internal leaders and partners
  • Leadership & mentoring — guides and develops AI practitioners across the CoE
  • Analytical problem-solving — applies structured thinking to ambiguous, multi-variable challenges
  • Influence without authority — shapes decisions and drives alignment across teams
  • Business acumen — translates complex technical concepts into measurable business value
  • Adaptability — stays effective and decisive in a fast-evolving AI landscape

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