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AI Integration Leader, MEA-Tr, Operations Integration & AI Transformation , MEA-Tr

Unlock employer Dubai, United Arab Emirates Direct to Company 1 hour ago · 28 Sep 2026

Financial

  • Estimate: $120k - $180k*
  • Zero income tax location

Accessibility

  • Office Only
  • Visa Provided

Requirements

  • Experience: Senior
  • English: Professional

Position

About the Role
The company's WW Operations AI portfolio is valued at $1B over a 3-year period across North America, Europe, and International Operations. The Middle East, Africa, Turkey, and Rest of World (MEATR) region is entering a pivotal phase as it transitions from fragmented AI experimentation to a structured, P&L-accountable AI transformation program. We are seeking a technically proficient and operationally skilled Program Manager to lead a team of over 15 Business Intelligence Engineers (BIEs) in executing our AI integration roadmap across more than five countries. This role is not just strategic; it involves ownership of the build, deployment, measurement, and scaling of AI solutions that yield traceable dollar savings for the P&L.

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Key Responsibilities

  • Own the execution of the MEATR AI Transformation Roadmap from foundation through scale, fulfilling quarterly milestones and gated investment reviews.
  • Drive 3-5 AI pilot programs per phase across key countries, with a goal to scale successful pilots to production within 12 months.
  • Establish and maintain a three-tier governance cadence consisting of weekly country standups, monthly program reviews, and quarterly steering committee inputs.
  • Build and manage the KPI tracking dashboard, ensuring all initiatives are instrumented, measured, and appropriately attributed to P&L.

Technical Leadership & Architecture

  • Lead a team of 15+ BIEs in designing and deploying AI/ML solutions across supply chain, middle mile, and last mile operations.
  • Make technical decisions regarding data pipelines, API integrations, model selection, and platform architecture—this role requires hands-on technical fluency, not just program oversight.
  • Promote the use of a centralized tool registry and governance platforms, ensuring compliance and tracking of tool registration and reuse.
  • Architect solutions that align with 6 core operational pillars: Safety, Cost, Speed, Quality, Vendor Experience, Employee Experience.
  • Assess and implement business review automation tools and reporting platforms throughout MEATR countries.

Measurement & Financial Accountability

  • Enforce the three-tier financial validation chain: self-reported → Finance verification → regional Finance sign-off.
  • Oversee the AI Fluency Index implementation across MEATR, tracking five dimensions: Proficiency, Foundation Training, Usage, Personal Automation, and Responsible AI.
  • Ensure that every AI initiative evidences hard savings or efficiency savings—focusing on tangible metrics, avoiding vanity metrics.
  • Deliver cumulative finance-validated P&L savings within 12 months of program launch.

Workforce Enablement & Scaling

  • Create and execute the AI readiness scorecard (individual + organizational) across all MEATR countries.
  • Develop the AI Champions network, aiming for 30% of managers to become AI Builders and 10% of Builders to become AI Practitioners.
  • Initiate country-level AI Enablement programs that include structured onboarding curricula, office hours, and adoption tracking.
  • Achieve 95% weekly active usage of AI tools among managers.

Cross-Regional Coordination

  • Act as the MEATR representative in the global AI consortium, coordinating with regional pillar leads across unified workstreams.
  • Represent MEATR in global forums such as quarterly business reviews, AI strategy summits, and pillar working groups.
  • Ensure compliance of MEATR execution with global standards (intake fields, governance scoring, finance validation gates, standardized pillar metrics).

Basic Qualifications

  • Bachelor's degree or equivalent.
  • Experience managing large technical programs, especially within high-growth startups or large enterprises.
  • Familiarity with Data & AI related technologies, including AI/ML, GenAI, Analytics, Database, and/or Storage.

Preferred Qualifications

  • Master’s degree in operations research, applied mathematics, theoretical computer science, or equivalent; or a Doctorate/PhD or equivalent, along with 10+ years of experience managing scientists or machine learning engineers.
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