AVP, AI Quality & Reliability Engineering

Vizient; Edina (MN); On-site; USD 156,500 - 290,100; Full time

Benefits offered by this job

Comprehensive benefits plan

Job summary

Vizient is seeking an Associate VP to lead the strategy and operationalization of enterprise AI Quality Engineering capabilities. This role involves establishing scalable operating models and quality practices to support AI solutions at an enterprise scale.

The ideal candidate will partner closely with various teams to ensure AI solutions are secure, reliable, and compliant, while also driving modernization efforts in traditional Quality Engineering practices.

Qualifications

• Proven experience leading AI Quality Engineering initiatives.
• Ability to communicate effectively with technical and executive stakeholders.
• Strong understanding of AI validation and governance practices.

Responsibilities

• Lead enterprise AI Quality Engineering initiatives across Vizient.
• Define enterprise AI quality standards and testing methodologies.
• Partner with AI Engineering and Governance teams to ensure compliance.

Skills

AI Quality Engineering

Leadership

Governance

Testing methodologies

Collaboration

Education

Bachelor's degree or higher in a technical field

Tools

AI Testing Tools

Simulation Platforms

Job description

In this role you will lead the strategy, operationalization, governance alignment, and continuous evolution of enterprise AI Quality Engineering capabilities across Vizient. You will establish scalable AI Quality Engineering operating models, validation frameworks, runtime quality practices, synthetic data ecosystems, simulation-driven testing capabilities, and enterprise quality standards supporting responsible industrialization of AI‑powered business solutions at enterprise scale and enterprise AI test data modernization, synthetic data platforms, healthcare digital simulation ecosystems, and hospital twin capabilities supporting secure, realistic, and scalable AI validation. You will partner closely with AI Engineering & Delivery, AI Operations, Governance, Security, Clinical, Data, and Business teams to ensure AI solutions are secure, reliable, observable, compliant, scalable, and aligned with enterprise quality and healthcare operational expectations.

AI Quality Engineering Leadership

• Lead enterprise AI Quality Engineering initiatives across Vizient, including AI‑powered applications, LLM‑enabled workflows, intelligent automation solutions, agentic systems, and enterprise AI platforms.
• Establish and mature AI Quality Engineering capabilities, including AI‑native testing strategies, validation frameworks, runtime assurance practices, scalable operating models, and reusable quality accelerators.
• Modernize traditional Quality Engineering practices to support AI‑enabled workflows, probabilistic systems, intelligent orchestration, and evolving healthcare operational workflows.
• Define enterprise AI quality standards, testing methodologies, validation approaches, release readiness criteria, and governance‑aligned quality practices supporting scalable AI adoption across the enterprise.
• Provide executive oversight across AI validation, quality engineering, test automation, runtime quality monitoring, release readiness, and quality improvement initiatives.
• Lead organizational transformation efforts supporting the evolution of traditional QA capabilities toward AI‑native quality engineering and simulation‑driven validation practices.

AI Validation, Testing & Runtime Assurance

• Lead enterprise AI validation strategies, including functional validation, prompt testing, workflow testing, regression testing, runtime quality assurance, and production reliability practices.
• Partner with AI Engineering, AIOps, LLMOps, Security, Governance, Clinical, and Data teams to establish scalable quality engineering processes supporting enterprise AI development lifecycle management and production operationalization.
• Support enterprise AI runtime quality practices, including telemetry integration, monitoring alignment, incident coordination, release validation, deployment readiness assessments, and runtime reliability improvement initiatives.
• Drive modernization of enterprise test automation capabilities leveraging AI‑assisted testing, intelligent automation, reusable testing accelerators, scalable quality engineering frameworks, and measurable quality metrics.
• Support enterprise AI observability and evaluation initiatives to improve reliability, traceability, runtime visibility, and operational confidence across AI‑enabled systems.
• Collaborate with Clinical, Operational, and Engineering stakeholders to support validation approaches for healthcare workflows, payer operations, and AI‑enabled business processes.

AI Test Data, Synthetic Data & Simulation Platforms

• Lead enterprise strategies supporting AI test data modernization, synthetic data capabilities, simulation environments, and scalable testing ecosystems enabling secure, realistic, and enterprise‑grade AI validation.
• Oversee development of enterprise synthetic test data platforms, healthcare simulation ecosystems, and hospital twin environments supporting AI engineering, testing, validation, and deployment readiness.
• Partner with Data, Clinical, Engineering, Security, Governance, and AI teams to support scalable simulation frameworks, realistic operational testing scenarios, PHI‑safe validation environments, and AI‑enabled testing acceleration initiatives.
• Support development of simulated healthcare operational environments and hospital twin capabilities enabling workflow validation, operational stress testing, scenario simulation, and safe evaluation of AI‑enabled healthcare processes.
• Drive scalable approaches for synthetic data governance, simulation fidelity, test environment automation, and secure testing ecosystem management within regulated healthcare environments.

Governance, Risk & Responsible AI

• Partner with AI Governance, Risk, Compliance, Security, Clinical, and Operational stakeholders to support responsible AI practices, operational safeguards, human oversight controls, validation traceability, auditability, and secure deployment of AI solutions.
• Support development and implementation of enterprise AI quality controls, validation evidence processes, testing governance frameworks, risk mitigation practices, and quality review standards aligned with enterprise and regulatory expectations.
• Help establish scalable processes supporting secure, compliant, reliable, and measurable AI solution deployment within regulated healthcare environments.

Portfolio, Delivery & Organizational Scaling

• Lead AI Quality Engineering portfolio activities, including organizational planning, vendor coordination, contractor oversight, delivery prioritization, execution governance, and scalable capability development.
• Partner with enterprise stakeholders to evaluate implementation readiness, quality risks, scalability considerations, testing feasibility, and delivery dependencies for prioritized AI initiatives.
• Support tooling evaluations, platform assessments, automation strategies, and modernization initiatives supporting enterprise AI Quality Engineering maturity.
• Define scalable squad structures, delivery engagement models, support processes, and governance approaches supporting enterprise AI transformation initiatives.
• Help drive organizational capability development, workforce maturation, operating model evolution, and enterprise adoption of modern AI Quality Engineering practices.

Leadership, Communication & Culture

• Lead, mentor, and develop quality engineering leaders, managers, engineers, analysts, and contractor teams while fostering a collaborative, continuously learning, and engineering‑driven culture.
• Communicate quality risks, testing strategies, governance implications, implementation trade‑offs, and strategic recommendations effectively to both technical and executive stakeholders.
• Promote a culture of engineering excellence, continuous improvement, enterprise accountability, responsible AI adoption, and operational discipline.
• Research and evaluate emerging AI quality engineering, testing, observability, validation, simulation, automation, and runtime assurance technologies supporting innovation and continuous improvement initiatives.

Executive - Associate VP (E1)

Estimated Hiring Range: At Vizient, we consider skills, experience, and organizational needs in our compensation approach. Geographic factors may adjust the range estimate and hires typically fall below the top range. Compensation decisions are tailored to individual circumstances. The current salary range for this role is $156,500.00 to $290,100.00. This position is also incentive eligible.

Vizient has a comprehensive benefits plan! Please view our benefits here: http://www.vizientinc.com/about-us/careers