AI Product Owner

Key Responsibilities1. Product Ownership & Backlog Management

• Own the product vision and roadmap for assigned AI products within APAC.
• Translate business requirements, customer needs, and commercial opportunities into epics, user stories, and acceptance criteria.
• Create, maintain, and prioritise the product backlog based on business value, scalability, and delivery feasibility.
• Act as the final decision maker on backlog prioritisation and scope trade-offs.

2. Agile Delivery & Iteration

• Work closely with Engineering, Data Science, Design, and Delivery teams to ensure clear, actionable requirements ahead of sprint execution.
• Lead and participate in backlog refinement, sprint planning, sprint reviews, and retrospectives.
• Enable fast build-measure-learn cycles through incremental delivery and feedback loops.
• Ensure delivery aligns with agreed timelines, capacity, and quality standards.

3. AI Product Commercialisation

• Drive customer-facing AI product readiness, including MVP definition, feature packaging, and rollout sequencing.
• Partner with commercial and go-to-market teams to ensure AI capabilities are demoready and usable by customers and partners.
• Support pilots and early launches, capturing feedback and optimising adoption.
• Track and optimise outcomes such as usage, conversion uplift, automation rate, and operational efficiency.

4. Scalability & Reusability

• Design AI solutions with a build-once, reuse-many mindset across APAC markets.
• Identify opportunities where AI drives operational scalability and cost efficiency.
• Promote standardisation of features, APIs, and configurations to minimise market-specific customisation.

5. Stakeholder Management & Communication

• Act as the primary product interface between business stakeholders, technical teams, and delivery functions.
• Facilitate alignment across regional and global stakeholders on scope, priorities, risks, and dependencies.
• Communicate product progress and decisions using structured artefacts such as roadmaps and release notes.

Key Deliverables

• Product vision and roadmap
• Prioritised product backlog
• Sprint-ready requirements and clarifications
• Demoable AI product increments
• Adoption and performance insights
• Inputs to commercial rollout and scaling plans

Key Stakeholders

• Product Management, Engineering & Data Science, Platform & Delivery Teams, Operations,
• Commercial / Sales / Go-to-Market, Security, Privacy, and Compliance
• External (as required): Customers, distribution partners, and AI technology vendors