AVP, Engineering

Vizient•Chicago, IL

2d•$156,500 - $290,100

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 role owns engineering strategy and execution for a modern, AI-native, cloud-scalable, data-driven analytics ecosystem intended to reduce client data acquisition burden, improve data quality and trust, and provide healthcare leaders with timely, actionable insights. The AVP leads engineering execution aligned with the CPSC modernization roadmap, spanning 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. The role establishes the technical foundation and engineering practices to deliver these capabilities securely and at enterprise scale. As the domain's senior technical leader, the AVP is accountable for engineering excellence, architecture, delivery capability, and consistent execution across multiple engineering teams. The position translates product and enterprise strategy into executable technology roadmaps, leads complex cross-team initiatives, establishes modern PDLC/AIDLC and AI-first engineering practices, and drives adoption of cloud-native, data, API, and AI technologies. The AVP builds and scales a high-performing engineering organization, develops Engineering Managers and technical leaders through coaching and performance management, and strengthens engineering capabilities across the domain. The role partners 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 adopting 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 designing and operating 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 in 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

Hold weekly 1:1s with Engineering Managers.
Coach Engineering Managers on technical leadership and people management.
Manage Engineering Managers’ performance and career development.
Recruit and develop management talent.
Assess team health and support organizational design.
Implement AI-first development patterns in partnership with enterprise AI platform providers.
Coordinate cross-team technical architecture and dependencies with Architecture.
Align technical roadmaps quarterly within the domain cluster.
Assess technical risks and plan mitigations.
Establish standards and best practices across teams.
Escalate and resolve complex technical problems.
Conduct quarterly delivery reviews and goal setting.
Coordinate cross-team complex initiatives.
Discuss resource allocation and priorities with Engineering Managers.
Serve as an escalation point for delivery risks and impediments.
Communicate delivery status to stakeholders.
Participate in VP review meetings and organizational initiatives.
Promote cross-domain collaboration and knowledge sharing.
Make process improvement and scaling decisions.
Interface with business unit stakeholders alongside Product.
Lead engineering strategy and execution for modernization of the Operational Benchmarking Platform.
Establish engineering practices and technical foundations to deliver platform capabilities securely and at enterprise scale.
Translate product and enterprise strategy into technology roadmaps and lead complex cross-team initiatives.
Drive adoption of cloud-native, data, API, and AI technologies.
Build and scale a high-performing engineering organization and strengthen engineering capabilities across the domain.
Partner with Product, Architecture, Data, AI, Security, and business leaders to ensure solutions are secure, scalable, interoperable, compliant, and aligned with technology strategy.