Product Manager, AI Transformation
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About the Role
AI Transformation Squad | Dubai, UAE | Full-time We're hiring a Product Manager to lead the AI Transformation Squad, the team responsible for turning AI from a buzzword into a b.
Key Skills for This Role
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Overview
AI Transformation Squad | Dubai, UAE | Full-time
We're hiring a Product Manager to lead the AI Transformation Squad, the team responsible for turning AI from a buzzword into a business lever at eyewa.
This is an execution role, not a strategy role.
You'll build AI-powered internal tools that eliminate manual work, reduce cost, and improve operational decisions across the business, working across Operations, CX, Marketing, Supply Chain, and Finance.
You'll also be eyewa's internal authority on how AI gets shipped, defining the governance standards and best practices that every product team follows when productionising AI features.
The mandate is broad.
The team is lean.
The expectation is hands-on ownership from day one.
Key Responsibilities
- Define and own the AI transformation roadmap across ops, CX, supply chain, and data intelligence, sequenced by ROI with clear stakeholder alignment
- Translate cross-functional business problems into precise AI product specs: datasets, model objectives, output format, evaluation criteria, integration points
- Lead technical design discussions with ML engineers on trade-offs between model approaches, latency, accuracy, and cost
- Build, launch, and iterate on agentic workflows and intelligent automation that internal teams actually adopt and rely on
- Own AI output quality in production: define what "production-ready" means, build evaluation frameworks, and monitor accuracy, hallucination rate, latency, and reliability
- Be the requirements funnel: collect and prioritise AI requests from across the business, push back on low-ROI use cases, and protect ML engineering time
- Define success metrics for every initiative before building: cost saved, time recovered, resolution rate, error reduction, NPS uplift
- Own eyewa's AI governance framework: output quality standards, evaluation criteria, monitoring requirements, explainability expectations, and production-readiness protocols
- Evangelise AI best practices across product teams: run enablement sessions, build playbooks, and act as the go-to partner when any squad is productionising an AI feature
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