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Vizient, Inc.
Senior AI Quality & Reliability Engineer
Career Insights for Systems Engineer
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Based on Minnesota data
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What they do
A Systems Engineer creates computer and data communication networks for companies and organizations. Plans and designs layout for a network, determines the hardware needed and placement of computers, servers, cables and routers; determines data storage, system capacity, and speed.
$103,348 / year median in Minnesota
-15% projected decline
Job Description
Senior AI Quality & Reliability Engineer Vizient, Inc. 7601 France Ave S Ste 500 (Show on map) Jul 24, 2026 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 drive the hands-on design, development, and execution of AI Quality Engineering initiatives supporting Vizient's enterprise AI transformation efforts. You will design and implement AI Quality Engineering practices, AI validation processes, AI-assisted testing approaches, runtime quality controls, and scalable testing frameworks that support the responsible deployment of AI-powered business solutions. This role combines hands-on quality engineering, AI-enabled testing modernization, healthcare workflow validation, technical mentorship, and cross-functional collaboration. You will help advance Vizient's Quality Engineering capabilities beyond traditional software testing toward AI-native validation, AI-assisted testing, runtime observability, reliability engineering, and modern AI Quality Engineering practices. Responsibilities Design, develop, and execute AI Quality Engineering strategies supporting AI-powered applications, large language model (LLM) solutions, intelligent automation, agentic systems, and enterprise AI platforms.
Build and implement scalable AI Quality Engineering practices, including AI-native testing approaches, validation processes, runtime quality controls, reusable testing accelerators, and automated testing frameworks.
Lead AI validation activities including functional testing, prompt validation, workflow testing, regression testing, release validation, runtime quality assurance, and production reliability support.
Partner with AI Engineering, AIOps, LLMOps, Security, Governance, Clinical, Data, and Product teams to deliver scalable AI Quality Engineering processes across enterprise AI initiatives.
Support runtime reliability through observability, telemetry, distributed tracing, monitoring, drift detection, incident response, and operational quality assurance for AI-enabled systems.
Develop and maintain AI evaluation frameworks, validation datasets, quality scoring methodologies, and automated testing workflows that improve the reliability and scalability of AI solutions.
Collaborate with Clinical, Operational, and Engineering stakeholders to validate healthcare workflows, payer operations, and AI-enabled business processes while supporting responsible AI deployment through human-in-the-loop validation practices.
Coordinate testing activities across Agile delivery teams, including sprint planning, test execution, defect management, issue tracking, release readiness, risk identification, and production support.
Mentor Quality Engineers and provide technical guidance that promotes engineering excellence, AI-enabled testing modernization, continuous improvement, and adoption of modern Quality Engineering practices.
Research, evaluate, and recommend emerging AI Quality Engineering, testing automation, observability, and runtime assurance technologies to continuously improve enterprise AI quality capabilities. Qualifications Relevant degree preferred. Advanced degree in Computer Science, Engineering, or a related field highly preferred. Bachelor's degree in Computer Science,
5 or more years of experience in Quality Engineering, Quality Assurance, software testing, enterprise application delivery, technology operations, or related technology functions required.
2 or more years of experience providing technical leadership for testing initiatives, automation programs, or enterprise technology delivery projects required.
Experience supporting Quality Engineering or Quality Assurance across enterprise platforms, APIs, healthcare applications, operational workflows, or integrated business systems required.
Strong knowledge of software development life cycle (SDLC), Agile methodologies, test automation frameworks, defect management, release validation, and production support processes required.
Experience validating AI-powered applications, intelligent automation, machine learning, large language model (LLM), or AI-enabled business workflows preferred.
Experience with AI Quality Engineering practices, AI-assisted testing, runtime observability, monitoring, telemetry, or reliability engineering preferred.
Strong analytical, problem-solving, organizational, communication, collaboration, and leadership skills required.
Demonstrated ability to manage multiple priorities and deliver results within fast-paced, highly collaborative enterprise environments required.
Experience in healthcare technology, payer operations, clinical workflows, or other regulated industries supporting AI governance and responsible AI deployment preferred. #LI-JB1