1) Product Discovery & Rapid Validation (AI-Accelerated)
Lead structured discovery: define problems, map journeys, prioritize opportunities, and validate solutions before building.
Run lightweight discovery cycles (3–5 days or 1 week): problem framing → prototype/wireframe → quick user validation → decision.
Translate research into clear product insights, constraints, and tradeoffs (clinical, compliance, operational, commercial).
2) Data-Driven Growth & Experimentation
Own metric-driven iteration across acquisition, activation, conversion, retention, revenue, referral .
Define measurement plans: events, funnels, cohorts, dashboards; ensure instrumentation is in place.
Run experiments (A/B tests where possible): hypotheses, success metrics, rollout plans, and post-analysis.
3) Strategy, Roadmap, and Financial Impact
Define product strategy and roadmap aligned to company OKRs, capacity, and financial outcomes.
Evaluate initiatives with expected impact: revenue uplift, retention improvement, cost reduction, operational efficiency, risk reduction.
Maintain a clear prioritization system (e.g., RICE/ICE/Opportunity Scoring) and communicate tradeoffs with C-level.
4) Cross-Functional Collaboration & Stakeholder Alignment
Partner closely with engineering, design, data, clinical/ops, sales, marketing, and customer success to ensure product decisions support company objectives and real customer needs.
Drive decision clarity: define the problem, options, tradeoffs, and risks (incl. compliance/clinical), and make recommendations; escalate effectively when needed.
Align internal and external stakeholders (e.g., enterprise clients/partners) via structured discovery sessions, feedback loops, and clear documentation of scope, timelines, and success metrics.
Oversee releases to ensure alignment between product and go-to-market teams (launch readiness, enablement, comms, support prep).
5) Developer Collaboration & Delivery Excellence (Agile)
Translate discovery into delivery with developers and designers: PRDs, user stories, acceptance criteria, edge cases, and non-functional requirements.
Maintain delivery hygiene: backlog quality, sprint ceremonies, QA readiness, bug triage, release monitoring, and post-release learnings.
Ensure measurement is built-in (event tracking, dashboards, experiment setup) — not added after launch.
6) AI-Driven Development & Modern Shipping
Operate an AI-augmented product workflow to improve cycle time and quality (without outsourcing thinking).
Use AI responsibly to accelerate: research synthesis, PRD drafting, user story refinement, analytics/query assistance, experiment design, QA test cases, release notes, and stakeholder comms.
Partner with engineering on practical AI-enabled delivery practices (as appropriate): AI-supported estimation, test planning, triage, documentation, and release workflows.
Enforce guardrails: privacy, security, accuracy checks, and risk awareness—especially for mental health use cases.
7) Team & Culture
Help build a customer-driven culture: continuous discovery, fast learning loops, crisp writing, and decision clarity.
Build/mentor/manage a product team (PMs, UX/UI) as needed and raise the quality bar for product practice.
Requirements
2+ years experience as a Product Manager / Product Owner shipping digital products.
Proven ability to run product discovery (research → synthesis → rapid validation → decision).
Strong understanding of Agile principles and hands-on backlog management.
Excellent communication, presentation, and leadership skills (written + verbal; executive-ready).
Sharp analytical and problem-solving skills: funnels/cohorts/retention, prioritization, and experiment interpretation.
Demonstrated experience using AI tools in real product work (discovery, writing specs, analysis, QA, release support) with strong judgment and source-checking.
Passion for improving mental health outcomes in Thailand (and willingness to learn clinical/ethical context).
Comfortable with…