QA Automation Engineer – Agentic AI, UI, and API
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What you'll do
- Design and execute quality engineering strategies for AI-powered applications, agentic AI systems, user interfaces, APIs, LLM-enabled workflows, intelligent automation, and integrated enterprise platforms.
- Develop scalable test automation frameworks, reusable testing accelerators, validation processes, and automated workflows that improve quality, efficiency, and test coverage.
- Implement AI validation approaches, including functional, prompt, workflow, integration, regression, and human-in-the-loop testing, along with validation datasets and quality evaluation methods.
- Advance AI-assisted testing and modern quality engineering practices that address nondeterministic AI behavior, intelligent orchestration, and evolving healthcare workflows.
- Support runtime quality and reliability through telemetry, distributed tracing, observability, monitoring, drift detection, incident analysis, and production validation.
- Collaborate with engineering, AIOps, LLMOps, security, governance, data, clinical, and operational clients to integrate quality practices throughout the software and AI development lifecycle.
- Coordinate test execution, defect management, release validation, risk identification, and production support activities across AI-enabled solutions.
- Evaluate and implement testing, automation, observability, and AI quality engineering tools and technologies that improve scalability, reliability, and traceability.
- Mentor quality engineers and analysts by providing technical guidance, sharing automation practices, and fostering continuous learning and engineering discipline.
- Communicate quality risks, technical findings, implementation dependencies, and recommendations to technical and business clients while promoting continuous improvement and responsible AI adoption.
What they're looking for
- Experience designing and executing quality engineering strategies for AI-powered applications and agentic AI systems.
- Proficiency in developing scalable test automation frameworks and reusable testing accelerators.
- Experience with AI validation approaches, including prompt, workflow, integration, and human-in-the-loop testing.
- Knowledge of runtime quality and reliability practices, including telemetry, distributed tracing, and observability.
- Ability to collaborate with cross-functional teams including engineering, AIOps, LLMOps, and clinical stakeholders.
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
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.
Responsibilities:
- Design and execute quality engineering strategies for AI-powered applications, agentic AI systems, user interfaces, APIs, LLM-enabled workflows, intelligent automation, and integrated enterprise platforms.
- Develop scalable test automation frameworks, reusable testing accelerators, validation processes, and automated workflows that improve quality, efficiency, and test coverage.
- Implement AI validation approaches, including functional, prompt, workflow, integration, regression, and human-in-the-loop testing, along with validation datasets and quality evaluation methods.
- Advance AI-assisted testing and modern quality engineering practices that address nondeterministic AI behavior, intelligent orchestration, and evolving healthcare workflows.
- Support runtime quality and reliability through telemetry, distributed tracing, observability, monitoring, drift detection, incident analysis, and production validation.
- Collaborate with engineering, AIOps, LLMOps, security, governance, data, clinical, and operational clients to integrate quality practices throughout the software and AI development lifecycle.
- Coordinate test execution, defect management, release validation, risk identification, and production support activities across AI-enabled solutions.
- Evaluate and implement testing, automation, observability, and AI quality engineering tools and technologies that improve scalability, reliability, and traceability.
- Mentor quality engineers and analysts by providing technical guidance, sharing automation practices, and fostering continuous learning and engineering discipline.
- Communicate quality risks, technical findings, implementation dependencies, and recommendations to technical and business clients while promoting continuous improvement and responsible AI adoption.
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 $102,400.00 to $179,000.00.This position is also incentive eligible.
Vizient has a comprehensive benefits plan! Please view our benefits here:
http://www.vizientinc.com/about-us/careers
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.
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