Role & seniority: Senior/lead QA leader (8+ years QA, 3+ in leadership) responsible for strategic QA across software, data, and AI; DevOps-aligned culture champion.

Stack/tools: Playwright, UFT, ALM; Azure DevOps; SAP; CI/CD integration; automated testing, data quality checks, AI model testing in deployment pipelines.

Top 3 responsibilities

Define and implement end-to-end QA strategy for software, data, and AI aligned with business goals and DevOps practices.
Build, mentor, and manage a high-performing QA team; collaborate with product, software, data science, and operations to ensure quality across lifecycle.
Drive continuous improvement in QA processes, tooling, and automation; oversee data quality, data governance, and AI model testing within pipelines.

Must-have skills

Leadership experience in QA within a fast-paced/Agile DevOps environment.
Strong experience with test automation, CI/CD, and QA tooling (Playwright, UFT, ALM, Azure DevOps).
Data quality governance, validation techniques, and experience integrating QA with data pipelines.
Familiarity with AI/ML concepts, model evaluation metrics, bias detection, and responsible AI testing.
Excellent communication and stakeholder management.

Nice-to-haves

Deep experience with performance and security testing tools; AI model testing in DevOps pipelines; governance and ethics aspects of AI.
Location & work type: Fully onsite in Holland, MI. On-site role only. Salary range: $10

Full Description

Description

Strategic Leadership

Define and implement the overall QA strategy, encompassing software, data, and AI, aligning with company goals and industry best practices. Champion a culture of quality across the organization, fostering collaboration and a proactive approach to quality assurance within a DevOps framework.

Software Quality Assurance

Develop and implement comprehensive test strategies for software applications, covering functional, regression, performance, security, and usability testing, integrated within our CI/CD pipelines.
Introduce and manage appropriate testing tools and automation frameworks to enhance efficiency and coverage, ensuring seamless integration with our DevOps processes.

Data Quality Management

Establish and enforce data quality standards across all data sources, pipelines, and storage systems, incorporating data quality checks into our DevOps pipelines.
Design and implement data quality checks, validation processes, and data governance procedures, ensuring alignment with our DevOps practices.
Monitor data quality metrics, identify anomalies, and lead root cause analysis and resolution efforts, collaborating closely with DevOps teams to address any infrastructure-related issues.

AI Model Quality Assurance

Define and implement testing strategies for AI models, encompassing accuracy, bias detection, explain-ability, fairness, and robustness, integrating these tests into our model deployment pipelines.
Establish metrics and benchmarks for evaluating AI model performance and ensure compliance with ethical AI principles, working closely with data science and DevOps teams to ensure responsible AI development and deployment.

Team Leadership & Collaboration

Build, manage, and mentor a high-performing team of QA professionals, providing guidance, training, and development opportunities, fostering a DevOps mindset within the team.
Collaborate closely with product management, software development, data science, and operations teams to ensure seamless integration of quality throughout the product lifecycle, promoting a culture of shared responsibility for quality within the DevOps framework.

Continuous Improvement

Stay abreast of emerging technologies, industry trends, and best practices in software quality, data quality, and AI model testing, particularly in the context of DevOps and continuous delivery.
Drive continuous improvement initiatives to enhance QA processes, methodologies, and tools, leveraging automation and DevOps principles to optimize efficiency and effectiveness.

Skills

Quality Assurance Manager