AVP, Engineering

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Vizient is seeking an experienced and transformational AVP of Engineering to lead the modernization of its Clinical Practice and Ambulatory Domain's Operational Benchmarking Platform. This leader will own the engineering strategy and execution required to build a modern, AI-native, cloud‑scalable, data‑driven, and highly intuitive analytics ecosystem that reduces client data acquisition burden, improves data quality and trust, and enables healthcare leaders to make better decisions through timely, actionable insights.

The AVP will lead engineering execution aligned with the CPSC modernization roadmap, including automated data acquisition and ingestion, scalable data engineering and pipelines, AI-enabled mapping and normalization, ontology‑driven data models, advanced benchmarking, guided analytics, and a command‑center‑style executive experience. This role will establish the technical foundation and engineering practices needed to deliver these capabilities securely and at enterprise scale.

As the senior technical leader for the domain, the AVP will be accountable for engineering excellence, architecture, delivery capability, and consistent execution across multiple engineering teams. The role will translate product and enterprise strategy into executable technology roadmaps, lead complex cross‑team initiatives, establish modern PDLC/AIDLC and AI‑first engineering practices, and drive adoption of cloud‑native, data, API, and AI technologies.

This leader will also be responsible for building and scaling a high‑performing engineering organization, developing Engineering Managers and technical leaders through coaching and performance management, and strengthening engineering capabilities across the domain. The AVP will serve as a key technology partner to Product, Architecture, Data, AI, Security, and business leaders, ensuring solutions are secure, scalable, interoperable, compliant, and aligned with Vizient’s broader technology strategy.

• Weekly 1:1s with Engineering Managers
• EM coaching on technical leadership and people management
• Performance management and career development for EMs
• Recruiting and developing management talent
  
  Team health assessment and organizational design

• Implement AI-first development patterns in partnership with enterprise AI platform providers.
• Cross-team technical architecture and dependency management (with architecture)
• Quarterly technical roadmap alignment within domain cluster
• Technical risk assessment and mitigation planning
• Standards and best practices across teams
• Complex technical problem escalation and resolution

• Quarterly delivery review and goal setting
• Cross-team coordination for complex initiatives
• Resource allocation and priority discussions with EMs
• Escalation point for delivery risks and impediments
• Stakeholder communication on delivery status

• VP review meetings and organizational initiatives
• Cross-domain collaboration and knowledge sharing
• Process improvement and scaling decisions
• Interface with business unit stakeholders (alongside product)

• Proven experience leading AI-first or AI-enabled product…