Product Manager

A. Product Strategy & Roadmap

. Define and maintain the product vision and roadmap for selected digital mental health and AI-enabled initiatives

. Translate strategic objectives into prioritised backlogs, epics and user stories with clear acceptance criteria.

. Review and adjust roadmap based on data, user feedback, and system constraints.

B. AI Product Design & Governance

. Define use cases for AI-enabled features (e.g., co-pilot tools, triage support, recommendation engines) grounded in clear problem statements and measurable outcomes.

. Work with data science and engineering teams to translate model capabilities and limitations into usable, safe product features.

. Ensure human-in-the-loop safeguards, escalation logic, explainability elements, and appropriate UX disclosures are embedded into product design.

. Define model evaluation metrics (e.g., precision/recall for risk alerts, response quality benchmarks, latency thresholds) and acceptance thresholds prior to deployment.

. Oversee responsible AI governance, including bias risk assessment, data provenance considerations, auditability, and monitoring for model drift.

C. Delivery & Cross-Functional Coordination

. Lead sprint planning, backlog grooming and prioritisation in collaboration with engineering, data science, UX, and operations teams.

. Define clear product requirements documents (PRDs), including data flows, edge cases, risk scenarios and non-functional requirements.

. Ensure alignment between frontend, backend, analytics and ML components.

. Coordinate UAT, stakeholder reviews, and release readiness sign-offs.

D. Data, Metrics & Impact Tracking

. Define north-star and operational KPIs (e.g., engagement, completion rates, workflow efficiency, response times, escalation accuracy).

. Work with analytics teams to measure user behaviour and AI system performance.

. Interpret data to guide iteration, feature sunsetting, or scaling decisions.

. Ensure product decisions are evidence-informed and evaluation-ready.

E. Documentation, Risk & Transition

. Maintain comprehensive documentation of product requirements, workflows, system dependencies and governance controls.

. Develop knowledge transfer artefacts to support long-term sustainability and ownership transitions.

. Identify operational, clinical and reputational risks associated with AI-enabled features and implement mitigation plans.

. Support audit, compliance, and security review processes.

F. User Research & Validation

. Conduct user research across help-seekers, counsellors, clinicians and administrators to validate needs and usability.

. Design and oversee pilots and controlled rollouts of new AI-enabled capabilities.

. Translate qualitative and quantitative findings into actionable product improvements.

. Ensure continuous feedback loops are embedded into product lifecycle.

. Coordinate with research partners to run evaluation studies of the deployed system.