20 days ago
Chicago, IL, USA +2 moreSenior
Base Salary
$102k - $179k/yr
Responsibilities
- Design and execute AI Quality Engineering strategies for AI-powered applications, LLM solutions, intelligent automation, agentic systems, and enterprise AI platforms.
- Build AI-native testing practices, validation processes, runtime quality controls, reusable testing accelerators, and automated testing frameworks.
- Lead functional, prompt, workflow, regression, release, runtime quality, and production reliability testing.
- Develop AI evaluation frameworks, validation datasets, quality-scoring methods, and automated testing workflows.
- Support runtime reliability through observability, telemetry, distributed tracing, monitoring, drift detection, incident response, and operational quality assurance.
- Validate healthcare workflows, payer operations, and AI-enabled business processes using human-in-the-loop practices.
- Coordinate sprint testing, defect management, issue tracking, release readiness, risk identification, and production support.
- Mentor Quality Engineers and provide technical guidance on AI-enabled testing modernization and Quality Engineering practices.
- Research and recommend emerging AI Quality Engineering, testing automation, observability, and runtime assurance technologies.
Requirements
- Bachelor's degree in Computer Science and at least 5 years of experience in Quality Engineering, Quality Assurance, software testing, enterprise application delivery, technology operations, or related technology functions.
- At least 2 years of technical leadership experience for testing initiatives, automation programs, or enterprise technology delivery projects.
- Experience supporting Quality Engineering or Quality Assurance across enterprise platforms, APIs, healthcare applications, operational workflows, or integrated business systems.
- Strong knowledge of software development life cycle, Agile methodologies, test automation frameworks, defect management, release validation, and production support processes.
- Experience validating AI-powered applications, intelligent automation, machine learning, LLM, or AI-enabled business workflows is preferred.
- Experience with AI Quality Engineering, AI-assisted testing, runtime observability, monitoring, telemetry, or reliability engineering is preferred.
- Healthcare technology, payer operations, clinical workflows, regulated-industry experience, and responsible AI or AI governance experience are preferred.
- An advanced degree in Computer Science, Engineering, or a related field is highly preferred.
- Strong analytical, problem-solving, organizational, communication, collaboration, leadership, prioritization, and delivery skills are required.
Benefits
- Comprehensive benefits plan.
- The position is incentive eligible.
- Geographic factors may adjust the salary range, and hires typically fall below the top of the range.
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