AVP, AI Quality & Reliability Engineering

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When you're the best, we're the best. We instill an environment where employees feel engaged, satisfied and able to contribute their unique skills and talents while living and working as their authentic selves . We provide extensive opportunities for personal and professional development, building both employee competence and organizational capability to fuel exceptional performance through an inclusive environment both now and in the future. 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. In this role you will combine enterprise quality engineering leadership, AI-enabled testing modernization, healthcare workflow validation, governance alignment, and cross-functional organizational leadership. 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 simulatio

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