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Director Product Management - AI

Sedgwick · Texas, United States · 4 days ago
RemoteRemoteMarketingFull-time

About the role

Join Sedgwick, a company dedicated to helping people face unexpected challenges. As a Director Product Management – AI, you’ll be part of a team that transforms enterprise data into valuable insights using AI and modern data products.

Primary Purpose

The Director, Product Management – AI Enabled Enterprise Data Products is responsible for defining and executing the product strategy, roadmap, and business outcomes for Sedgwick’s enterprise AI-enabled data product portfolio. This role bridges business strategy, data strategy, AI innovation, technology execution, governance, and client value realization.

Essential Functions and Responsibilities

  • Define Product Vision and Strategy

  • Own the multi-year vision, strategy, roadmap, business model, and investment priorities for enterprise AI and data products.

  • Establish a product portfolio that enables business users, clients, and operational teams to discover, access, share, and analyze trusted enterprise data.

  • Drive AI-powered analytical experiences that allow users to interact with enterprise data through natural language and conversational interfaces.

  • Partner with executive leadership to identify opportunities that improve decision-making, efficiency, client experience, revenue growth, and cost optimization.

  • Develop business cases, success measures, portfolio-level OKRs, and executive communications on progress, risks, and architectural implications.

  • Oversee, coordinate & support development work

  • Own product portfolio KPIs and contributions to Product Group and enterprise OKRs, including quality, efficiency, sustainability, and value delivery.

  • Ensure solutions comply with enterprise security, privacy, regulatory, governance, and responsible AI requirements.

  • Serve as the senior escalation point for product-related dependencies, risks, and prioritization conflicts.

  • Own Enterprise Data Product Portfolio

  • Establish product management practices for enterprise data products, including data-as-a-product principles.

  • Define and manage reusable, governed data products supporting claims, finance, compliance, operations, client, and executive reporting needs.

  • Drive adoption of semantic models, business glossaries, metadata, cataloging, and self-service analytics capabilities.

  • Lead product strategy for enterprise data-sharing solutions for internal consumers, clients, partners, and third-party integrations.

  • Ensure data products are reliable, scalable, discoverable, secure, usable, and supported by lineage and governance.

  • Drive AI Analyst and Conversational Analytics Capabilities

  • Own the product vision for AI-powered analytics that provide trusted answers, insights, metrics, visualizations, and recommendations through natural language interactions.

  • Partner with business teams to identify high-value analytical use cases and decision-support opportunities.

  • Define requirements for semantic layers, knowledge models, retrieval experiences, governance controls, trust mechanisms, and user experiences.

  • Measure AI product effectiveness through adoption, accuracy, user satisfaction, business impact, and operational efficiency.

  • Ensure AI-generated insights are explainable, governed, auditable, and aligned with enterprise policies.

  • Enable Secure Enterprise Data Sharing

  • Define strategy and roadmap for enterprise-scale data exchange and sharing capabilities.

  • Partner with Security, Governance, Privacy, and Legal teams to establish secure and compliant data-sharing frameworks.

  • Drive capabilities for role-based access, entitlements, auditing, lineage, masking, client access controls, and data-sharing agreements.

  • Enable governed data product distribution across business units, clients, partners, and external ecosystems while supporting growth, performance, compliance, and resilience.

  • Stakeholder Engagement and Value Realization

  • Build strong relationships with business leaders, claims operations, finance, client services, technology leaders, and external stakeholders.

  • Translate business objectives and operational challenges into actionable AI and data product strategies.

  • Communicate roadmap progress, risks, dependencies, investment needs, and outcomes to executive leadership.

  • Establish and monitor portfolio-level KPIs, OKRs, and value realization metrics that trace strategy through implementation to business impact.

  • People Leadership

  • Lead and develop Product Owners, Scrum Masters, and product delivery teams.

  • Establish product management best practices across AI, data, analytics, and platform teams.

  • Coach teams on customer-centric product development, Agile practices, outcome-based planning, and value measurement.

  • Foster a culture of innovation, experimentation, accountability, continuous learning, and collaboration.

Qualifications

  • Education & Licensing:

  • Bachelor's degree in Business, Computer Science, Information Systems, Engineering, Data Science, or related field required.

  • Master's degree preferred.

  • Experience:

  • 10+ years of progressive experience in Product Management, Data Products, Analytics Platforms, AI Products, or Enterprise Technology.

  • 5+ years leading Product Managers or Product Owners and managing product portfolios.

  • Experience owning enterprise-scale data, analytics, AI, platform, reporting, self-service analytics, semantic modeling, AI/ML, or conversational AI products.

  • Experience defining product strategy, roadmaps, business cases, and measurable outcomes for data-driven products.

  • Experience working in Agile or scaled Agile environments and leading cross-functional teams across Architecture, Data Engineering, Analytics, Security, Governance, and Business stakeholders.

  • Skills & Knowledge:

  • Expert knowledge of Agile methodologies, product operating models, portfolio management, prioritization, roadmap development, and outcome measurement.

  • Deep understanding of Data as a Product principles, modern data platforms, data mesh, data fabric, governance, semantic modeling, metadata, lineage, and enterprise analytics architectures.

  • Strong understanding of AI, generative AI, conversational analytics, augmented decision-support platforms, and responsible AI practices.

  • Experience with enterprise data sharing, security, privacy, governance, compliance frameworks, and risk management.

  • Strong executive communication, stakeholder management, product adoption, organizational change, and people leadership capabilities.

  • Ability to balance business value, technical complexity, investment, risk, and operational impact.

Success Measures

  • Delivery of a clear enterprise AI and data product strategy, roadmap, and investment plan.

  • Adoption and measurable business value from AI-enabled analytics, data products, and data-sharing capabilities.

  • Improved data product quality, usability, discoverability, governance, security, and scalability.

  • Effective stakeholder alignment, executive communication, prioritization, and value realization.

  • Development of high-performing product teams and consistent product management practices.

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