AI Product Owner

Job Summary About the Role Key Responsibilities Product Vision Strategy

• Define and own the product vision, strategy, and roadmap for AI-enabled LH capabilities, ensuring alignment with Swiss Re's broader business objectives
• Identify and prioritize high-value AI use cases across underwriting, in-force management, operations, and portfolio monitoring
• Translate business strategy into a clear, actionable product roadmap and investment priorities
• Balance short-term delivery goals with long-term platform and capability development to ensure sustainable growth

Business Ownership Value Realization

• Act as the primary business owner for AI-enabled products, championing their value across the organization
• Define measurable success metrics, KPIs, and value realization targets to track and demonstrate impact
• Ensure AI solutions generate actionable recommendations that meaningfully support business decision-making
• Continuously assess business outcomes and adapt priorities based on realized value and stakeholder feedback
• Drive business adoption and lead change management activities to embed AI capabilities into everyday workflows

Product Planning Backlog Management

• Own and prioritize the product backlog, defining epics, features, user stories, and MVP scope with precision and clarity
• Collaborate with stakeholders to shape ideas and convert them into actionable, well-scoped delivery plans
• Make smart prioritization decisions that balance business value, risk, complexity, and delivery capacity
• Ensure tight alignment between business objectives and technical execution at every stage

AI Product Orchestration

• Coordinate execution across AI Engineers, Data Engineers, Data Scientists, Business Analysts, and business stakeholders
• Ensure smooth handoffs between data foundations, model development, AI engineering, and business adoption activities
• Facilitate decision-making across multiple teams and stakeholder groups to keep delivery on track
• Manage dependencies and remove blockers that could impact product delivery timelines or quality

Governance, Risk Quality Oversight

• Ensure AI products adhere to governance, compliance, privacy, and model risk management requirements
• Oversee production readiness and release decisions with a rigorous quality mindset
• Champion responsible AI practices, explainability requirements, and appropriate controls and guardrails
• Embed monitoring and change management processes to support sustainable AI operations

Stakeholder Engagement Communication

• Build trusted relationships with business leaders across underwriting, actuarial, operations, and in-force management functions
• Communicate product vision, roadmap, and progress clearly and compellingly to diverse stakeholder audiences
• Translate complex AI concepts and business implications into accessible language for non-technical audiences
• Serve as the primary point of accountability for business stakeholders, ensuring transparency and trust

About the Team About You We are looking for candidates who meet these requirements:

• 8+ years of experience in product ownership, business analysis, digital transformation, data analytics, or AI-enabled business solutions
• Strong Life Health insurance or reinsurance domain expertise, including a solid understanding of underwriting, claims, actuarial, operations, and in-force management processes
• Proven product management and delivery experience as a Product Owner, Product Manager, or Lead Business Analyst, with a strong track record of managing product roadmaps, backlogs, and Agile delivery environments
• Strong AI data literacy, including a working understanding of AI, GenAI, machine learning, analytics, and data platforms, with the ability to engage effectively with Data Scientists, AI Engineers, and Data Engineers
• Exceptional stakeholder management and communication skills, with demonstrated ability to influence, negotiate, and facilitate across diverse, senior stakeholder groups in matrixed organizations

These are additional nice to haves:

• Experience delivering AI-powered decision-support solutions in a complex business environment
• Familiarity with portfolio monitoring or in-force management use cases within LH reinsurance
• Knowledge of model governance, explainability, and regulatory frameworks relevant to AI in financial services
• Experience working in global reinsurance organizations with cross-functional, international teams

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.