AI Product Lead - Generative AI

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AI Summary

Join a large, highly ambitious organisation investing heavily in AI as a core capability across the business. As an AI Product Lead, you will head up the Generative AI roadmap and take full ownership of getting complex AI products into production. You will operate at the intersection of AI engineering, platform architecture, and product leadership.

Key Highlights
Head up Generative AI roadmap
Take full ownership of AI products
Operate at the intersection of AI engineering, platform architecture, and product leadership
Key Responsibilities
Define and frame real business problems into AI-solvable solutions
Work directly with engineers on architecture decisions
Own delivery of AI capabilities
Lead adversarial testing and ensure robustness in production
Continuously optimise performance post-launch
Technical Skills Required
AI engineering Platform architecture Product leadership RAG systems Conversational AI Agentic systems Model and architecture trade-offs AI evaluation and testing methodologies
Benefits & Perks
Up to 70k AED p/month
Bonus
Education allowance
Air tickets
Visa/medical for self & family
Relocation assistance

Job Description


AI Product Lead - Generative AI


💰 Up to 70k AED p/month (equivalent to 230k USD p/annum net)

👪 Benefits include: Bonus, education allowance, air tickets and visa/medical for self & family)

📍 Abu Dhabi (relocation assistance provided)


We are hiring an AI Product Lead to join an enterprise organisation in Abu Dhabi to head up their Generative AI roadmap. This isn’t a typical Product role - it’s for someone who can sit with AI engineers, challenge architecture decisions, and still take full ownership of getting complex AI products into production.


It’s a high impact role within a central team focused on advancing future readiness through secure and scalable AI adoption 🚀


Discover the company

You’ll be joining a large, highly ambitious organisation investing heavily in AI as a core capability across the business. With dozens of live and emerging use cases, they’re building a centralised AI function designed to scale reusable capabilities across customer experience, operations, and internal productivity.


This is not experimentation at the edges - it’s enterprise-wide AI transformation, with real backing, real scale, and real impact 🌍


Discover the role

The mandate is simple (but not easy): build and own AI capabilities end-to-end.


Think less “product lines” and more platform-level capabilities - conversational AI, enterprise RAG systems, agentic workflows, and AI-driven automation 🤖


You’ll operate at the intersection of:

  • AI engineering ⚙️
  • Platform architecture 🏗️
  • Product leadership 📊


This is the kind of role where you can define the problem, shape the solution with engineers, and be accountable for how it performs in the real world.


Discover the responsibilities

You’ll take full ownership of AI products from idea through to optimisation:

  • Define and frame real business problems into AI-solvable solutions
  • Work directly with engineers on architecture decisions (RAG, pipelines, models, orchestration)
  • Own delivery of AI capabilities - not just specs or roadmaps
  • Design and implement evaluation frameworks (accuracy, hallucination, latency, cost) 📈
  • Lead adversarial testing and ensure robustness in production
  • Continuously optimise performance post-launch
  • Drive workshops with stakeholders, then translate outcomes into clear execution for engineering teams


The expectation is clear: once you’ve done your part, engineers should be able to go and build - with no ambiguity.


Discover the requirements

This role is intentionally selective - they are not looking for a generic Product Manager.


You’ll likely have:

  • A strong engineering foundation before moving into product
  • Proven experience (at least 3 years) delivering GenAI products into production
  • Deep understanding of:

-RAG systems (chunking, retrieval, ingestion pipelines)

-Conversational AI and agentic systems

-Model and architecture trade-offs

-AI evaluation and testing methodologies

-The ability to challenge engineers and architects credibly 💬

-A track record of owning outcomes - not just contributing


If you’ve built AI products end-to-end and want a bigger, more complex playground - this is it 🎯


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