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

Amazon’s worldwide Operations organisation has committed roughly $1B over three years to embedding AI across its fulfillment, transportation, and sortation network in North America, Europe, and the International regions — and this role extends that program into the Middle East and Africa transformation (MEA-Tr) cluster from Amazon’s Dubai hub. The AI Integration Leader sits between central AI and machine learning teams and the operators who run sites on the ground, turning a global roadmap into changes that actually work on a warehouse floor or a delivery station in the UAE and the wider region.

Day to day, the job is less about building models and more about making them stick: working with regional operations leadership to identify where a forecasting tool, a routing algorithm, or a computer-vision quality check can remove a manual step, then owning that change end to end — coordinating with vendors and central engineering, building the training materials a site needs, and tracking whether the new process actually holds once the launch excitement fades.

It suits someone who has run real operations — has stood on a fulfillment center floor or managed a transportation network — but is equally comfortable in a room with data scientists, translating “the model predicts X” into “here’s what changes for the shift supervisor on Tuesday.” Change management experience matters as much as technical fluency; the hard part of operations AI is rarely the algorithm, it’s getting a regional network of sites to adopt it consistently.

Success in this role looks like adoption rates, not pilot counts — sites using the new tool a year after launch, not just the ones that tried it once.

Amazon's operations network runs on thin margins per unit moved, so small efficiency gains compound fast across a region the size of MEA. Every process this role helps automate or improve — a forecasting model that gets staffing right before a demand spike, a routing change that shaves minutes off a delivery route, a quality check that catches errors before they reach a customer — reduces cost-to-serve at a scale where fractions of a percent matter. Poorly integrated AI is arguably worse than no AI: a model site teams don't trust or don't use is money spent for nothing, and a change that gets pushed through without buy-in creates workarounds that undermine the whole program. This role is the difference between a central AI investment that shows results in the MEA region and one that stalls at the pilot stage. Getting it right also builds the case, internally, for further AI investment in a region that has historically had smaller initiatives than Amazon's larger, more mature operating geographies — meaning the work done here has an outsized influence on what gets funded next.

This is a rare seat for someone who wants operations experience and AI-program experience on the same résumé, at a company that is investing at the billion-dollar scale in exactly this kind of work. The role gives direct exposure to how a Fortune-10 operations network actually adopts machine learning — not the theory, but the messy, cross-functional reality of getting a regional network of sites to change how they work. That combination of operational credibility plus technology-program fluency is genuinely scarce, and it opens two distinct career paths: deeper into regional operations leadership (site director, regional operations manager) or across into central program and product roles supporting AI and automation initiatives globally. Along the way, the person in this role builds a stakeholder network spanning central technical teams, regional leadership, and site operators — the kind of cross-functional relationship-building that is hard to manufacture and valuable well beyond Amazon. They'll also develop change-management skills that transfer to almost any operations-heavy industry moving toward automation: retail, logistics, manufacturing, and quick-commerce are all working through versions of this same problem. For someone early in an operations-leadership track, this is a chance to be closely associated with one of the company's flagship transformation programs at a formative stage in a growing region, which tends to be remembered when promotion conversations happen.

• Experience in operations, supply chain, or fulfillment management, ideally within a large, matrixed organisation
• Track record of leading process improvement or automation projects from pilot through to full rollout
• Comfort working with data science, engineering, or analytics teams without needing to build the models yourself
• Strong stakeholder management and change-management skills across multiple sites or regions
• Experience with performance metrics, lean, or continuous-improvement methodologies
• Bachelor’s degree in a related field; an advanced degree or relevant certifications are a plus
• Willingness to travel across the MEA region as programs roll out to different sites