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About the Role

Lead and develop a team of Quality Engineers while remaining hands-on in driving modern quality engineering practices across EHS & ESG software products. This role combines technical leadership, people management, and quality strategy, focusing on evolving Quality Engineering capabilities through innovative automation and AI-enabled testing solutions.

Responsibilities

• Lead, mentor, and develop a team of Quality Engineers, fostering a culture of ownership, collaboration, and continuous improvement.
• Define and execute the Quality Engineering strategy aligned with product and business objectives.
• Drive alignment of the Quality Engineering strategy across engineering teams for consistency, traceability, governance, and scalable quality practices.
• Champion modern QE practices, including shift-left testing, continuous testing, automation, and quality-by-design principles.
• Establish quality standards, processes, and best practices across engineering teams.
• Monitor, measure, and drive adoption of Quality Engineering standards and best practices, using data and reporting for continuous improvement.
• Drive continuous improvement initiatives to increase product quality, reliability, and delivery efficiency.
• Remain technically engaged by contributing to automation frameworks, testing approaches, and quality engineering solutions.
• Design, implement, and improve automated testing strategies across UI, API, contract, integration, regression, and end-to-end testing.
• Evaluate and introduce AI-powered testing tools and techniques to improve test coverage, efficiency, and defect detection.
• Explore the use of AI for test generation, automation optimisation, defect analysis, and improving engineering productivity.
• Support the integration of automated testing into CI/CD pipelines.
• Troubleshoot complex quality challenges and provide technical guidance to QE Engineers and development teams.
• Partner with Software Engineering, Product Management, DevOps, and Architecture teams to embed quality throughout the SDLC.
• Influence engineering teams to adopt quality-first practices and shared ownership of testing.
• Analyse quality trends, identify risks, and drive data-informed improvements.
• Define and monitor quality metrics, KPIs, and dashboards.
• Leverage reporting and analytics tools, including Power BI, to provide actionable quality insights and support data-driven decision making.
• Communicate quality insights and recommendations to senior leadership.
• Recruit, coach, and develop Quality Engineering talent.
• Conduct regular performance reviews and support career progression.
• Build technical capability within the QE team through mentoring and knowledge sharing.

Requirements

• Proven experience managing and mentoring Quality Engineering, Software QA, or Test Engineering teams.
• Strong hands-on experience with software testing and automation.
• Experience designing and maintaining automation frameworks using technologies such as Playwright, Cypress, Selenium, or similar.
• Experience with API testing, automation, and contract testing in distributed or microservices-based architectures.
• Experience integrating automated testing into CI/CD pipelines.
• Strong understanding of Agile software development methodologies.
• Experience implementing Quality Engineering strategies across enterprise software products.
• Experience defining and measuring quality metrics and KPIs.
• Strong analytical, reporting, and data visualisation skills, with experience using tools such as Power BI to derive insights from quality metrics and communicate performance trends.
• Ability to balance technical delivery with team leadership responsibilities.
• Strong analytical and problem-solving skills.
• Practical experience applying AI tools within software testing or engineering workflows.
• Understanding of AI-assisted testing approaches, including AI-generated test cases and scenarios, automated test optimisation, intelligent defect analysis, AI-assisted automation development, and improving engineering productivity through AI tools.
• Curiosity and enthusiasm for adopting emerging technologies to improve software quality.
• A passion for engineering excellence and delivering high-quality software.
• A balance of technical expertise and strong people leadership.
• The ability to inspire teams while remaining hands-on and technically credible.
• A continuous improvement mindset with a focus on automation, innovation, and AI-enabled quality practices.
• The ability to influence cross-functional teams and drive meaningful change.
• Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.

Skills

• Playwright
• Cypress
• Selenium
• API testing
• Contract testing
• CI/CD integration
• Agile methodologies
• Quality metrics and KPIs
• Power BI
• AI tools in software testing
• AI-assisted testing
• Test generation
• Automation optimisation
• Defect analysis
• Engineering productivity through AI
• Enterprise SaaS applications
• Cloud-based applications
• Distributed systems
• Azure
• AWS
• Google Cloud
• Performance testing
• Security testing
• Accessibility testing
• Reliability testing
• Jira
• Azure DevOps
• TestRail
• Xray
• Tricentis Tosca
• Tricentis qTest
• ISTQB certification
• AI-focused learning
• Generative AI training

Location

• Onsite (potential requirement at a Wolters Kluwer office)

Work Type

• Full-time

Experience Level

• Manager
• Leadership

Education Level

• ISTQB certification (or equivalent Quality Engineering certification) is desirable.
• Relevant AI-focused learning or certifications (such as Anthropic Academy or equivalent Generative AI training) would be an advantage.

About the Company

• Support customers managing critical Environmental, Health, Safety, and Sustainability processes.