Vice President, AI Context Content Management

Purpose: Responsible for building and governing the enterprise knowledge foundation that powers AI-generated insights. This role oversees the capture, curation, structure, and lifecycle management of business knowledge, ensuring organizational expertise, business processes, policies, rules, and contextual information are transformed into trusted, AI-consumable assets. The leader is accountable for enterprise knowledge strategy and execution, data governance, metadata strategy, and content that powers the AI context layer. The leader will serve as a strategic bridge between business teams, analytics organizations, and engineering partners to ensure enterprise knowledge is accurate, current, discoverable, and aligned with authoritative sources of truth. The leader will drive strategic advantage from enterprise knowledge assets to position the organization at the forefront of AI-enabled decision-making and agentic production. AI Content Development and Strategic Execution Own Enterprise Knowledge Strategy and AI Content Management, balancing strategic vision with operational execution to transform institutional knowledge into a strategic asset that creates competitive advantage and accelerates AI adoption. Identify, document, and transform critical institutional knowledge into scalable information assets, developing and maintaining domain-specific knowledge bases that include business context, taxonomies, knowledge-to-data mappings, and metric standards. Establish an information lifecycle management framework for knowledge assets designed to intake, curate, validate, evolve, and retire content while preserving integrity and minimizing bias through drift prevention, relevance management, and continuous validation. Partner with technology teams to map institutional knowledge and information assets to trusted data sources that power generative and agentic AI solutions Possess AI literacy and apply conceptual knowledge of retrieval-augmented generation (RAG), vector databases, and content optimization techniques to structure information assets for retrieval accuracy and AI effectiveness. Influence, Collaboration, and Stakeholder Management Collaborate cross-functionally with data engineering, analytics, and business leadership to ensure alignment and prioritization of AI content knowledge creation and data governance efforts. Discover and translate AI business needs and use cases into explicit knowledge requirements by domain, and partner to gather and document key information into reusable AI context assets Communicate on progress, barriers, opportunities, and outcomes surrounding knowledge strategy and governance policies to senior leadership and other key stakeholders. Embedded Data Governance Maintain a robust data governance framework to ensure data accuracy, consistency, and security in all Data Products, Analytics Products, and AI insights. Enable data users by maintaining a dynamic data and metrics catalogue, providing enablement and training opportunities, and offering issue support and resolution. Partner with data engineering to close data quality gaps and embed governance early in data layer creation. Foster a culture of data stewardship and accountability throughout the organization. Ensure data and knowledge assets are leveraged effectively to enable Centene's business and AI goals. Develop and enforce data ownership policies, usage standards, and best practices across the organization.

Leadership and Development Lead, grow, and develop a high-performing team of data governance specialists and data analysts. Guide and align individual and team level goals to organizational strategic direction. Provide mentorship and professional development opportunities to team members. Promote a culture of continuous improvement and innovation across the data organization and in the business units. Performs other duties as assigned. Comply with all policies and standards.

Bachelor's degree