This position is responsible for ensuring that AI-enabled signals, observation tools and Child360 capabilities strengthen day-to-day practice and child support decisions without crossing into labelling, scoring, or diagnostic use.
The position oversees product direction and sets clear judgment boundaries for how signals and insights are designed, interpreted, and applied in early childhood contexts, so tools remain practical decision support for educators and child support teams. This role works closely with Child Development, Data, Tech, Child Support Services, Operations and external partners to translate curriculum and child development priorities into scalable, operationally viable products.
The role also entails evaluating pilot outcomes in real settings and recommending whether to scale, refine, pause, or stop based on usability, impact, and sustainability.
Key Job Responsibilities
Portfolio Direction and Prioritisation
- Translate curriculum and portfolio priorities into clear product objectives tied to measurable educator and child development outcomes
- Prioritise initiatives based on observed classroom friction, workload pressure, reinforcement gaps, and child development needs
- Define what improvement looks like in practical terms such as time saved, clearer next steps, improved prioritisation, or reduced rework
End to End Product Ownership
- Lead discovery, MVP build, and live validation in real centre and child support contexts
- Review pilot evidence and determine whether initiatives improve practice under real conditions
- Drive documented decisions to scale, refine, constrain, pause, or exit
Problem Framing and Value Definition
- Frame clear problem statements grounded in educator workflows and broader child development realities
- Articulate practical value for educators, child development teams, and families
Innovation Framing and Responsible AI Guardrails
- Set boundaries for how AI-enabled tools and signals may be used in classroom and child support contexts
- Ensure products function as decision support and not scoring, diagnostic, or surveillance mechanisms
- Maintain alignment with curriculum priorities and child development principles
Outcome Delivery and Measurement
- Define measurable outcomes such as workload reduction, clarity gained, and faster decision cycles
- Build measurement into products to track real impact, not activity metrics such as clicks or logins
- Use evidence to inform scale and investment decisions
Commercial and Extension Oversight
- Support packaging, positioning, and pricing logic for extensions beyond core provision
- Monitor cost to serve and avoid bespoke, non-scalable builds
- Ensure commercialisation does not distort pedagogy or educator workflow
Cross Functional Execution
- Coordinate delivery across Tech, Data, Child Development, CSS, and Operations
- Manage dependencies, trade-offs, and delivery readiness across initiatives
- Keep roadmaps and sequencing explicit to reduce misalignment
Leadership Communication and Decision Support
- Surface risks and trade-offs early with supporting evidence
- Provide concise, decision ready recommendations to senior leadership forums
What Success Looks Like
- MVPs are deployed in real centre and child development workflows, not just demonstrated
- Educators report practical improvements such as time saved, clearer next steps, or reduced documentation friction
- Child development teams receive earlier, usable signals that help prioritise and act, without labelling or scoring children
- Each initiative has defined metrics and a documented scale, refine, pause, or stop decision
- Responsible AI guardrails are reflected in product design and real usage
- Roadmaps, priorities, and trade-offs remain clear and aligned across functions
- Senior leadership receives concise updates backed by real usage and outcome evidence
Qualifications And Job Requirements
EDUCATION & EXPERIENCE
- Bachelor's degree in a relevant discipline (e.g., Business Administration, Data Science, Computer Science, Engineering, Information Systems) or equivalent practical experience
- 812 years of relevant experience in product management or product ownership, including meaningful exposure to AI-enabled or data-driven products
- Experience operating in education, public sector, or other regulated environments is advantageous
What We Are Looking For
- Strong product judgement, able to frame problems clearly and make disciplined trade-offs under uncertainty
- Strong bias to action, able to move from intent to shipped MVPs quickly while keeping scope tight
- Demonstrated experience running structured MVP cycles with clear hypotheses, outcome measures, and scale decisions
- Able to translate strategic intent into practical execution plans and usable outcomes for educators and child support teams
- Working fluency with data and AI concepts, including signals, evaluation logic, risk boundaries, and misuse scenarios
- Resilient under ambiguity and setbacks, able to iterate, recover quickly, and keep delivery moving
- Strong stakeholder leadership and influence across cross-functional and senior team
- Commercial awareness, including understanding scalable business models and cost-to-serve considerations
- Comfortable operating in a lean, high-accountability environment with minimal hierarchy
- Clear written and verbal communication suited for executive-level discussions
WHY THIS ROLE IS UNIQUE
- Build within a newly formed function focused on genuine 0-to-1 product creation
- Own and set the AI standards, signals, and guardrails early, with the authority to align teams.
- Operate in a nimble team with high ownership and direct exposure to senior leadership
- Shape products that have measurable impact on educator workload, child development clarity, and family trust
- Combine disciplined governance with entrepreneurial execution
