Chubb
Product Owner – Knowledge Repository & Management Platform
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About Chubb
Chubb is the world's largest publicly traded property and casualty insurance company, with operations in 54 countries and territories. As an underwriting company, Chubb assesses, assumes, and manages risk with insight and discipline. Our technology organization is at the forefront of transforming how institutional knowledge is captured, governed, and operationalized to power AI at enterprise scale.
Role Overview
The Product Owner – Knowledge Repository & Management Platform is a senior, strategic role responsible for defining and delivering Chubb's enterprise-wide Knowledge Repository — the foundational AI-ready knowledge layer powering the broader Chubb AI ecosystem.
This platform enables the capture, governance, and operationalization of enterprise knowledge at scale — connecting structured and unstructured content across lines of business and geographies into a governed, machine-interpretable, and reusable knowledge layer. It supports advanced analytics, intelligent automation, and AI-driven decision-making across the enterprise.
The Product Owner will own the product vision, roadmap, and delivery lifecycle for this platform — operating at the intersection of AI, data engineering, knowledge management, and enterprise governance.
Key Responsibilities
Product Strategy & Roadmap
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- Own and communicate the end-to-end product vision, strategy, and roadmap for the Knowledge Repository platform, aligned to Chubb's AI readiness goals and the Target Operating Model (TOM)
- Define and sequence delivery milestones toward the 2027 strategic objective: a scalable, enterprise-wide knowledge layer deployed globally across lines of business and geographies
- Translate business needs from across the organization into platform capabilities that are governed, scalable, and AI-consumable
Backlog & Agile Delivery
- Develop, maintain, and prioritize the product backlog across functional and non-functional requirements — covering the Integration Fabric, Knowledge Graph, Search, Permissions, Governance, Observability, APIs, and MCP layers
- Author clear, well-groomed user stories with defined acceptance criteria; lead sprint planning, estimation, retrospectives, and scrum-of-scrums ceremonies
- Work closely with engineering, data, and AI teams to clarify requirements, unblock delivery, and ensure platform quality
Knowledge Architecture & Governance
- Define and enforce governed taxonomies, metadata models, and ontologies to ensure findability, consistency, and AI-readiness across knowledge assets
- Establish data contracts between knowledge producers and consumers, capturing lineage, quality standards, source ownership, and access controls
- Partner with Legal, Compliance, and Information Security to ensure all knowledge management practices meet regulatory and data governance requirements across global jurisdictions
- Develop and enforce policies for the secure handling, classification, and sharing of knowledge assets
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Stakeholder Engagement & Adoption
- Engage business stakeholders across the organization to understand knowledge gaps, capture institutional expertise, and prioritize platform investments
- Drive adoption through change management, communication, and measurable usage metrics; develop techniques to increase platform consumption and reduce SME dependency
- Develop a chargeback or value attribution model to align knowledge platform costs to lines of business
AI Enablement
- Ensure the Knowledge Repository provides structured, confidence-scored, and permission-aware knowledge to enterprise AI tools and platforms via APIs and MCP interfaces
- Collaborate with AI and data science teams to ensure knowledge assets are machine-interpretable — linking structured enterprise data with unstructured business content across the organization
- Support the enterprise goal of enabling comprehensive, context-aware decision-making powered by AI across business functions
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