Job description

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. Summary In this role, you will lead the day-to-day execution and delivery of AI Quality Engineering initiatives supporting Vizient s enterprise AI transformation efforts. You will help ehelp implement AI Quality Engineering practices, AI validation processes, AI-assisted testing approaches, runtime quality controls, and scalable testing frameworks supporting responsible deployment of AI-powered business solutions. This role combines hands-on quality engineering leadership, AI-enabled testing modernization, healthcare workflow validation, team leadership, and cross-functional delivery coordination to ensure the reliability, performance, and governance of AI-enabled systems. Responsibilities Lead day-to-day AI Quality Engineering activities supporting AI-powered applications, LLM-enabled workflows, intelligent automation solutions, agentic systems, and enterprise AI platforms. Implement AI Quality Engineering practices, including AI-native testing approaches, validation processes, runtime quality controls, reusable testing accelerators, and scalable testing workflows. Coordinate AI validation efforts, including functional testing, prompt testing, workflow validation, regression testing, defect management, release readiness, and production quality assurance. Partner with AI Engineering, AIOps, LLMOps, Security, Governance, Clinical, Data, and Product teams to ensure scalable and effective quality engineering processes across AI initiatives. Support runtime quality and reliability through observability, monitoring, telemetry analysis, incident support, drift detection, distributed tracing, and continuous improvement initiatives. Drive adoption of AI-assisted testing, intelligent automation, reusable test assets, and modern quality engineering practices that improve efficiency and quality outcomes. Lead delivery coordination activities including sprint execution, testing planning, issue tracking, risk identification, dependency management, and release support. Collaborate with clinical, operational, and engineering stakeholders to validate healthcare workflows, payer operations, and AI-enabled business processes while supporting responsible AI deployment. Mentor quality engineers, analysts, contractors, and delivery teams while fostering a culture of continuous learning, engineering excellence, and operational accountability. Qualifications Bachelor s degree in Computer Science, Information Systems, Engineering, or related field preferred. 7 or more years of experience in Quality Engineering, Software Testing, Quality Assurance, or related technology disciplines required. 1 or more years of experience supporting AI Quality Engineering, AI testing, AI validation, AI-enabled automation, or modern AI engineering initiatives preferred. Strong experience supporting Quality Engineering or Quality Assurance activities across enterprise platforms, APIs, operational workflows, healthcare applications, or integrated business systems required. Experience with enterprise testing practices, test automation frameworks, SDLC methodologies, Agile delivery models, defect management, release validation, and production support coordination required. Strong analytical, organizational, communication, collaboration, and leadership skills required. Ability to manage multiple priorities within fast-paced, evolving, and highly collaborative enterprise environments required. Experience with Python, APIs, automation frameworks, AI-enabled workflows, or modern software engineering practices preferred. Experience supporting AI/ML platforms, orchestration frameworks, runtime monitoring, observability tooling, or AI operational support processes preferred. Familiarity with AI-assisted testing, AI evaluation approaches, prompt testing, runtime observability, operational monitoring, drift detection, or AI operational assurance practices preferred. Experience supporting enterprise modernization or transformation initiatives involving AI, automation, or operational scaling preferred. #LI-JB1 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 $88,900.00 to $155,500.00. This position is also incentive eligible. Vizient has a comprehensive benefits plan! Please view our benefits here: vizientinc.com Equal Opportunity Employer: Females/Minorities/Veterans/Individuals with Disabilities The Company is committed to equal employment opportunity to all employees and applicants without regard to race, religion, color, gender identity, ethnicity, age, national origin, sexual orientation, disability status, veteran status or any other category protected by applicable law.

Requirements

Must-haves

Lead day-to-day AI Quality Engineering activities supporting AI-powered applications, LLM-enabled workflows, intelligent automation solutions, agentic systems, and enterprise AI platforms.
Implement AI Quality Engineering practices, including AI-native testing approaches, validation processes, runtime quality controls, reusable testing accelerators, and scalable testing workflows.
Coordinate AI validation efforts, including functional testing, prompt testing, workflow validation, regression testing, defect management, release readiness, and production quality assurance.
Partner with AI Engineering, AIOps, LLMOps, Security, Governance, Clinical, Data, and Product teams to ensure scalable and effective quality engineering processes across AI initiatives.
Support runtime quality and reliability through observability, monitoring, telemetry analysis, incident support, drift detection, distributed tracing, and continuous improvement initiatives.
Drive adoption of AI-assisted testing, intelligent automation, reusable test assets, and modern quality engineering practices that improve efficiency and quality outcomes.
Lead delivery coordination activities including sprint execution, testing planning, issue tracking, risk identification, dependency management, and release support.
Collaborate with clinical, operational, and engineering stakeholders to validate healthcare workflows, payer operations, and AI-enabled business processes while supporting responsible AI deployment.
Mentor quality engineers, analysts, contractors, and delivery teams while fostering a culture of continuous learning, engineering excellence, and operational accountability.
7 or more years of experience in Quality Engineering, Software Testing, Quality Assurance, or related technology disciplines required.
Strong experience supporting Quality Engineering or Quality Assurance activities across enterprise platforms, APIs, operational workflows, healthcare applications, or integrated business systems required.
Experience with enterprise testing practices, test automation frameworks, SDLC methodologies, Agile delivery models, defect management, release validation, and production support coordination required.
Strong analytical, organizational, communication, collaboration, and leadership skills required.
Ability to manage multiple priorities within fast-paced, evolving, and highly collaborative enterprise environments required.
Vizient has a comprehensive benefits plan! Please view our benefits here:
Equal Opportunity Employer: Females/Minorities/Veterans/Individuals with Disabilities

Nice-to-haves

Bachelor s degree in Computer Science, Information Systems, Engineering, or related field preferred.
1 or more years of experience supporting AI Quality Engineering, AI testing, AI validation, AI-enabled automation, or modern AI engineering initiatives preferred.
Experience with Python, APIs, automation frameworks, AI-enabled workflows, or modern software engineering practices preferred.
Experience supporting AI/ML platforms, orchestration frameworks, runtime monitoring, observability tooling, or AI operational support processes preferred.
Familiarity with AI-assisted testing, AI evaluation approaches, prompt testing, runtime observability, operational monitoring, drift detection, or AI operational assurance practices preferred.
Experience supporting enterprise modernization or transformation initiatives involving AI, automation, or operational scaling preferred.

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Keywords to mirror

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Platform: workday
Effort: long

Benefits

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Professional Development