AVP, Engineering

Vizient•Edina, MN

About The Position

Vizient is seeking an experienced, transformational AVP of Engineering to lead modernization of the Clinical Practice and Ambulatory Domain’s Operational Benchmarking Platform. The AVP will own the engineering strategy and execution to build a modern, AI-native, cloud-scalable, data-driven 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 an executive command-center experience. The role will establish the technical foundation and engineering practices 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 AVP 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. The role will build and scale a high-performing engineering organization, develop Engineering Managers and technical leaders through coaching and performance management, and strengthen engineering capabilities across the domain. The AVP will partner with Product, Architecture, Data, AI, Security, and business leaders to ensure solutions are secure, scalable, interoperable, compliant, and aligned with Vizient’s broader technology strategy.

Requirements

Proven experience leading AI-first or AI-enabled product and platform transformations, including adoption of AI across engineering and product development.
Deep expertise in cloud-native architecture and engineering across AWS, Azure, and/or Google Cloud Platform.
Deep expertise in data engineering, including design and operation of large-scale, high-performance data pipelines and platforms.
Deep expertise in Databricks, including modern lakehouse architectures, data processing, analytics, and enterprise-scale implementations.
Strong expertise in API-driven architecture and ecosystem design, including scalable integration patterns and platform interoperability.
Experience delivering technology solutions within regulated industries, preferably healthcare.
Strong understanding of enterprise data governance, privacy, security, risk, and regulatory compliance.
Demonstrated ability to build, scale, and lead high-performing engineering organizations, including talent development and organizational transformation.
Experience implementing and evolving modern Product Development Life Cycle (PDLC), SDLC, DevSecOps, and AI Development Life Cycle (AIDLC) practices.
Experience establishing AI-enabled engineering practices, including AI-assisted software development, testing, automation, and engineering productivity.
Strong understanding of modern distributed systems, microservices, event-driven architectures, and scalable platform engineering principles.
Proven ability to work effectively across hybrid, geographically distributed, and cross-functional teams, partnering closely with Product, Architecture, Data, Security, and business stakeholders.

Responsibilities

Lead engineering strategy and execution for modernization of the Clinical Practice and Ambulatory Domain’s Operational Benchmarking Platform.
Lead delivery aligned with the CPSC modernization roadmap, including automated data acquisition and ingestion, data engineering and pipelines, AI-enabled mapping and normalization, ontology-driven data models, advanced benchmarking, guided analytics, and executive analytics experiences.
Establish the technical foundation and engineering practices needed to deliver capabilities securely and at enterprise scale.
Set engineering direction, architecture, delivery capability, and execution standards across multiple engineering teams.
Translate product and enterprise strategy into executable technology roadmaps and lead complex cross-team initiatives.
Establish modern PDLC/AIDLC and AI-first engineering practices and promote adoption of cloud-native, data, API, and AI technologies.
Build and scale a high-performing engineering organization, develop Engineering Managers and technical leaders, and strengthen domain engineering capabilities.
Hold weekly 1:1s with Engineering Managers and coach them on technical leadership and people management.
Manage Engineering Manager performance and career development; recruit and develop management talent; assess team health and organizational design.
Implement AI-first development patterns in partnership with enterprise AI platform providers.
Coordinate cross-team technical architecture and dependencies with Architecture; align quarterly technical roadmaps within the domain cluster.
Assess and mitigate technical risks, establish standards and best practices across teams, and resolve escalated complex technical problems.
Conduct quarterly delivery reviews and goal setting; coordinate complex cross-team initiatives; discuss resource allocation and priorities with Engineering Managers.
Serve as an escalation point for delivery risks and impediments and communicate delivery status to stakeholders.
Participate in VP review meetings and organizational initiatives; support cross-domain collaboration, knowledge sharing, process improvement, and scaling decisions.
Interface with business unit stakeholders alongside Product.
Partner with Product, Architecture, Data, AI, Security, and business leaders to ensure solutions are secure, scalable, interoperable, compliant, and aligned with broader technology strategy.