Sub Chapter Lead Product Ownership Management

About the role

Roche is looking for a Sub Chapter Lead Product Ownership Management in Sant Cugat del Vallès. The role combines people leadership, software engineering best practices, product management and emerging technology enablement. You will manage and coach a team of Product Owners across multiple squads and set the ways of working for product discovery and backlog management.

Key responsibilities

• Manage, mentor and coach Product Owners, run 1:1s, performance reviews, career pathing and hiring, and build a psychologically safe, high-ownership culture
• Define and maintain product management best practices, discovery frameworks and SOPs, and set standards for AI tool use in discovery and backlog management
• Work with Agile Coaches and Engineering Leads to improve squad velocity, cross-team dependencies and release quality
• Keep backlog health, user story definitions, acceptance criteria and KPI tracking consistent across squads
• Align product strategy and squad backlogs with business and clinical priorities, and guide teams in evaluating AI/ML capabilities and data-driven features
• Facilitate cross-squad discovery and work with clinical advisors, medical researchers and UX designers to turn complex healthcare workflows into scalable SaaS products

Required profile

• Proven experience managing, coaching or mentoring Product Owners or Product Managers in Agile or matrixed environments
• Experience scaling B2B/B2B2C SaaS products through multi-product expansion or platform growth
• Ability to learn complex domains quickly; HealthTech, MedTech, Life Sciences or regulated B2B is a major plus
• Strong communication with technical teams, commercial stakeholders and clinical experts, and with customers and product and operations teams
• Bachelor's degree in Business, Computer Science, Healthcare/Life Sciences, Design or equivalent practical experience

Required skills

• Full product lifecycle mastery: discovery, hypothesis validation, launch, metric tracking
• Discovery frameworks, OKRs, backlog health, user story definition and Agile/Scrum continuous delivery
• Practical understanding of AI/ML and generative AI tools, and guidance of teams on building intelligent product features
• Technical literacy and empathy for clinicians and researchers