AI Product Manager - Customer Strategy Department, Platform Strategy Supervisory Department (PFSD)

Job Description: Department Overview Rakuten Group, headquartered in Japan, serves approximately 100 million customers domestically and operates in 30 countries globally. We provide 70+ services across e-commerce, payments, financial services, telecommunications, media, and sports. We are hiring an AI Product Manager for the Platform Strategy Supervisory Department (PFSD), a corporate organization reporting to top management (COO/Vice Chairman office). PFSD is responsible for group-wide customer strategy and ecosystem growth initiatives, rather than operating any single service. In this role, you will leverage Rakuten’s core platform assets-Points, Coupons, Brand, and customer data-together with AI (machine learning, generative AI, and agent-like experiences) to build and scale products that deliver both customer value and business impact. *Corporate organization: cross-functional teams such as Corporate Planning, CEO Office, HR, General Affairs, Finance/Accounting, and Legal. Key Features of the Platform Strategy Supervisory Department 1. Discipline as a Professional Team: "5C" The Platform Strategy Supervisory Department Administration & Organization Section values five key principles as a professional team. By leveraging Rakuten's vast assets, the department aims to make a significant social impact and enhance customer satisfaction. The team fosters a culture of enjoying challenges, even in situations of high uncertainty. - Challenge to innovate - Customer-oriented - Concept-driven - Cross-functional - Commitment to results 2. Intentionality We prioritize delivering results through contributions to society, customers, colleagues, and stakeholders, fostering a culture that supports each other's growth and challenges. Department Recruitment Site (Job Descriptions, Member Interviews, etc.) (opens in new window) Position: Why We Hire We are expanding the team to accelerate AI product creation and growth-bringing Points/Coupons/Brand/Data to the next stage through machine learning, generative AI, and agent-like experiences. Mission - Do not “add AI for AI’s sake.” Determine whether AI is the best solution and continuously deliver outcomes through data, experimentation, and operational excellence. - Leverage Rakuten’s core assets across services to achieve both customer experience value (fun, confidence, convenience) and business KPIs (usage, customer development, revenue, program effectiveness, etc.). Attractiveness - Leverage Rakuten's massive platform assets (points/coupons/brands/data) to drive high-impact AI products across the group. - Drive products end-to-end with ownership, from hypothesis design to requirement definition, development promotion, verification, and improvement. - Design scalable operations (Trust/Quality/Governance) in high-uncertainty domains, making data- and experiment-driven decisions. Position Details Strategy & Planning - Structure ambiguous problems and decide the best approach (AI vs. non-AI), including preventing “over-AI” solutions. - Define value hypotheses, target experiences, and KPI trees (business KPIs + AI metrics). - Create AI PRDs clarifying use cases, constraints, risks, operational assumptions, and guardrails. Delivery & Execution - Own assigned AI product/features end-to-end: requirements, delivery direction, launch, and continuous improvement. - Define data requirements (necessary datasets, logging/measurement design, labels, gaps and quality issues) and drive execution with cross-functional teams (Data Science/ML Engineering/Backend/UX, etc.). - Operate an iteration loop based on A/B tests and online evaluation; make decisions and improve continuously. KPI Design & Impact Measurement - Take responsibility for key business outcomes (e.g., usage, engagement, CVR, program effectiveness, LTV). - Define and monitor AI proxy metrics (e.g., precision/recall, ranking metrics, task completion rate, hallucination rate) and manage performance degradation. - Clarify ROI and next actions based on experiments, quasi-experiments, and log analysis. Trust & Responsible AI (Baseline) - Embed privacy, security, compliance, prohibited cases, quality testing, and rollback plans into product design. - Design for continuous updates and operations (monitoring, alerts, re-evaluation). Stakeholder Management - Align with stakeholders across business, marketing, UX, engineering, legal, and security; manage progress, key issues, and risks. - Prepare recommendations, evidence, mitigation plans, and next actions to move decisions forward. Example Product Concepts - Personalized optimization of points/coupons (optimizing the entire experience from presentation to issuance and redemption). - Smart agent transformation of services like PointClub (proposing/promoting optimal point experiences, procedural support, self-service inquiry resolution) - Expanding brand asset experiences (e.g., Shopping Panda) through generative AI (crossing online/offline channels). - Advanced marketing/offer decision-making products leveraging group-wide data. Work Environment Platform Strategy Supervisory Department consists of approximately 70 members with a roughly balanced gender ratio. The average age is in the early 30s. More than half of the team members have joined Rakuten mid-career, and the organization has a strong onboarding and support environment for experienced hires. Team members come from diverse professional backgrounds, including strategy consulting, IT, platform businesses, startups, telecommunications, and content/media operations, creating a highly cross-functional and collaborative culture. *We offer a flex-time system (with core hours), enabling flexible work styles. Mandatory Qualifications: - Experience owning products with responsibility for business KPIs (revenue and/or customer satisfaction). - Product management or director experience for large-scale web/app or platform products. - Hands-on experience with requirements definition, delivery direction, and post-launch iteration with engineering/creative teams. - Strong data-driven decision making (A/B testing, measurement design, and trade-off decisions). - Foundational understanding of ML and/or generative AI (data dependency, probabilistic behavior, and operational degradation). - The ability to create products with a sense of urgency in uncertain environments. - The ability to integrate diverse perspectives (UX/Creative/Marketing/Business/Development) into unified thinking. - Ability to execute in uncertainty with speed, and synthesize across UX, creative, marketing, business, and engineering. - Problem-solving skills, drive, initiative. - Work experience in English. - Native Japanese skills. - Submission of Japanese Resume. Desired Qualifications: - Experience with personalization/recommendation/optimization or agent-like generative AI products. - Experience collaborating with ML Ops/Data Ops and data governance for scalable operations. - Experience with Responsible AI (privacy, security, bias, explainability). - Experience leading and mentoring team members (No formal management experience required). Other Information: Additional information on Location Rakuten Crimson House: Futako-Tamagawa Related Pages - Employee Benefits: (opens in new window) - Employee Conditions: (opens in new window) - Culture: (opens in new window) #corporate #strategyplanning #operationdiv #AI