About the Role
As a key player in the financial industry for over 50 years in the UAE, we are looking for an ambitious individual to take the lead in establishing and running our AI Factory. This role is essential in coordinating multiple agile AI squads to deliver AI agents iteratively and at scale while integrating innovative solutions that uphold our commitment to exceptional service and operational excellence. You will be responsible for managing the entire product lifecycle for AI agents, driving continuous improvement, and ensuring that AI solutions are embedded into real business processes, driving tangible improvements in productivity and customer experience.
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Responsibilities
- Establish and run the AI Factory, mobilising and coordinating multiple agile AI squads (product, engineering, data science, MLOps/LLMOps, UX, risk and change).
- Own and maintain the agent backlog, including epics/features/user stories, acceptance criteria, prioritisation, and release planning aligned to capacity and dependencies.
- Define a repeatable delivery lifecycle and “definition of done” for AI agents (design, build, testing, validation, risk sign-off, deployment, and post-release monitoring) with clear quality gates.
- Drive continuous improvement across squads (cycle time, throughput, quality, rework, cost per agent) to meet scale targets without compromising control, resilience, or customer outcomes.
- Own the end-to-end product lifecycle for AI agents, from problem definition and backlog creation to launch, adoption, and optimization.
- Translate business needs into clear product requirements, user stories, and acceptance criteria to guide delivery squads.
- Prioritize features and releases based on business value, operational impact, risk considerations, and cost efficiency.
- Define clear agent objectives, user needs, and success metrics for each AI agent.
- Ensure AI solutions are embedded into real business processes and drive tangible improvements in productivity, customer experience, risk management, or control effectiveness.
- Partner closely with technology teams, third-party vendors, and business stakeholders to ensure solutions are technically sound, scalable, and production-ready.
- Work with risk, compliance, and control functions to ensure AI agents meet policy, governance, and regulatory expectations throughout their lifecycle.
- Track post-deployment performance of AI agents against defined KPIs (e.g. time saved, quality improvements, error reduction, adoption) and drive iterative improvements based on outcomes.
- Drive adoption of AI agents into production workflows, partnering with business owners to redesign processes, define operating procedures, and embed human-in-the-loop controls where required.
- Define and execute enablement plans (communications, training, playbooks) to build confidence and capability across the bank and ensure sustained usage.
- Act as a trusted advisor to senior stakeholders on AI adoption, value, controls, and the organisational changes required to scale.
- Own delivery tracking and executive reporting against the AI Factory roadmap (milestones, risks, dependencies, and outcomes) for governance forums and senior management.
- Evaluate and manage third-party vendors and partners (including AI tooling and model providers), ensuring commercial value, technical fit, and alignment to the company’s standards and governance.
Requirements
Qualifications
- Bachelor’s degree in Business, Technology, Engineering, Data Science, or a related field.
- 8 to 10 years of proven experience as a Product Owner or Product Manager delivering AI-enabled or data-driven products in an agile environment.
- End-to-end product ownership experience, from problem definition and backlog management through production deployment, adoption, and optimization.
- Hands-on experience building and deploying AI agents, with demonstrated delivery using Microsoft Copilot Studio and Copilot Foundry.
- Experience partnering with cross-functional stakeholders (i.e., engineering, architecture, cybersecurity, risk, and compliance) to take AI solutions from idea to production.
- Strong grasp of agile delivery practices, including prioritisation, sprint planning, and scope trade-offs.
- Experience operating in regulated environments; banking or financial services preferred, with strong AI/agent delivery experience in other regulated industries also considered.
- Ability to define clear success metrics, track value realization post-deployment, and drive continuous improvement.
- Excellent stakeholder management and communication skills, including influencing senior leaders and clearly communicating delivery progress and trade-offs.
- Strong analytical mindset with a consistent focus on measurable business outcomes.
