Director AI Strategy

apartmentARADA placeDubai calendar_month 

Job Description

Role Overview

We are seeking a visionary Director AI Strategy to lead the development and execution of our organization's artificial intelligence roadmap. This role will be responsible for identifying AI-driven opportunities, aligning AI initiatives with business objectives, and overseeing the adoption of scalable, ethical, and high-impact AI solutions across the enterprise.

The ideal candidate combines deep technical understanding of AI/ML with strong business acumen, leadership capability, and experience driving digital transformation at scale.

Enterprise AI Strategy & Transformation
  • Define the enterprise AI operating model, including governance, funding mechanisms, delivery frameworks, and business ownership structures.
  • Develop and maintain a multi-year AI transformation roadmap aligned with corporate strategy, digital initiatives, and revenue growth objectives.
  • Establish an AI portfolio management framework to prioritize use cases based on business value, technical feasibility, data readiness, and risk profile.
  • Lead enterprise-wide AI maturity assessments and develop capability-building roadmaps across functions.
Generative AI & Emerging Technologies
  • Define the organization's Generative AI strategy, including LLM adoption, AI agents, copilots, knowledge management, and workflow automation.
  • Evaluate and drive adoption of foundation models, multimodal AI systems, retrieval-augmented generation (RAG), and agentic AI architectures.
  • Establish standards for prompt engineering, model evaluation, AI observability, and GenAI lifecycle management.
  • Identify opportunities for AI-driven product innovation and new digital revenue streams.
AI Governance & Responsible AI
  • Chair the AI Governance Council and establish policies for Responsible AI, model risk management, explainability, bias mitigation, and regulatory compliance.
  • Define enterprise standards for AI security, model governance, data lineage, auditability, and AI risk controls.
  • Ensure compliance with emerging AI regulations and industry best practices across all deployed AI solutions.
Value Realization & Commercial Impact
  • Develop AI business cases and value-tracking frameworks to measure revenue uplift, productivity gains, cost optimization, and customer experience improvements.
  • Establish AI KPIs, adoption metrics, and executive dashboards to monitor business impact and strategic outcomes.
  • Drive AI investment decisions and portfolio optimization through measurable ROI frameworks.
AI Architecture & Platform Strategy
  • Define the target-state AI architecture encompassing data platforms, MLOps, LLMOps, model serving, vector databases, and AI infrastructure.
  • Partner with technology leadership to establish scalable AI platforms and reusable enterprise AI capabilities.
  • Oversee AI vendor strategy, model selection frameworks, and strategic partnerships with hyperscalers and AI technology providers.
Executive & Board Engagement
  • Serve as the principal AI advisor to the Executive Committee and Board on emerging AI opportunities, risks, and investment priorities.
  • Lead executive AI literacy programs to build leadership understanding of AI capabilities, limitations, and strategic implications.
  • Translate complex AI concepts into actionable business strategies for senior stakeholders.

Qualifications & Experience

Education
  • Bachelor's degree in Computer Science, AI, Data Science, Engineering, or related field
  • Master's or PhD preferred
Experience
  • 10+ years of experience in technology, data science, or AI-related roles
  • Proven experience leading AI strategy or large-scale digital transformation initiatives
  • Strong track record of delivering AI/ML solutions with measurable business impact
  • Experience in stakeholder management at executive level
Technical Expertise
  • Deep understanding of AI/ML techniques (e.g., NLP, computer vision, predictive modelling)
  • Familiarity with modern AI technologies, platforms, and tools (e.g., cloud AI services)
  • Knowledge of data architecture, data governance, and analytics ecosystems
  • Experience with generative AI and large language models is highly desirable
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