Senior AI Quality & Reliability Engineer

Vizient, Inc

. Design, develop, and execute AI Quality Engineering strategies for AI-powered applications, LLM solutions, intelligent automation, agentic systems, and enterprise AI platforms .

Posted 10/19/2026full-timeUnited StatesSenior💰 $102,400 - $179,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in AI Quality Engineering strategies, including the development of automated testing frameworks and validation processes for AI-powered applications. Proficient in Agile methodologies and capable of providing technical leadership in quality assurance across enterprise platforms and healthcare workflows.

Highest-signal resume keywords

AI Quality EngineeringTest Automation FrameworksAgile MethodologiesQuality AssuranceHealthcare Technology

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Quality EngineeringSoftware TestingDefect ManagementRelease ValidationAI Evaluation FrameworksMachine LearningObservabilityTelemetryRegression TestingPrompt Validation

Soft Skills

Analytical SkillsProblem-SolvingOrganizational SkillsCommunication SkillsCollaboration

Tools & Technologies

AI-Powered ApplicationsIntelligent AutomationDistributed TracingMonitoringIncident Response

Industry Keywords

Healthcare WorkflowsPayer OperationsRegulated IndustriesAI GovernanceResponsible AI Deployment

Tech Stack

Tools & technologies

SDLC

About the role

Key responsibilities & impact

Design, develop, and execute AI Quality Engineering strategies for AI-powered applications, LLM solutions, intelligent automation, agentic systems, and enterprise AI platforms
Build scalable AI-native testing approaches, validation processes, runtime quality controls, reusable testing accelerators, and automated testing frameworks
Lead 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
Support runtime reliability through observability, telemetry, distributed tracing, monitoring, drift detection, incident response, and operational quality assurance
Develop AI evaluation frameworks, validation datasets, quality scoring methodologies, and automated testing workflows
Validate healthcare workflows, payer operations, and AI-enabled business processes using human-in-the-loop validation practices
Coordinate Agile testing activities including sprint planning, test execution, defect management, issue tracking, release readiness, risk identification, and production support
Mentor Quality Engineers and provide technical guidance
Research and recommend emerging AI Quality Engineering, testing automation, observability, and runtime assurance technologies

Requirements

What you’ll need

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 SDLC, Agile methodologies, test automation frameworks, defect management, release validation, and production support processes required
Experience validating AI-powered applications, intelligent automation, machine learning, 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
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

Benefits

Comp & perks

Comprehensive benefits plan
Incentive eligible
Extensive opportunities for personal and professional development