About the Role

As the Manager, Quality Engineering, you will lead and develop a team of Quality Engineers while remaining hands-on in driving modern quality engineering practices across our EHS & ESG software products.

This role combines technical leadership, people management, and quality strategy. You will be responsible for evolving our Quality Engineering capabilities by introducing innovative automation approaches, leveraging AI-enabled testing solutions, and embedding quality throughout the software development lifecycle.

Working closely with Engineering, Product Management, Architecture, and DevOps teams, you will help ensure we deliver secure, scalable, and reliable enterprise software solutions that support customers managing critical Environmental, Health, Safety, and Sustainability processes.

The successful candidate will be a passionate Quality Engineering leader who can coach and inspire a team while also getting involved technically to improve frameworks, automation, processes, and engineering practices.

Key Responsibilities

Quality Engineering Leadership

• Lead, mentor, and develop a team of Quality Engineers, creating 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 to ensure consistency, traceability, governance, and scalable quality practices throughout the organisation.
• 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 to identify opportunities for continuous improvement.
• Drive continuous improvement initiatives to increase product quality, reliability, and delivery efficiency.

Hands-on Technical Contribution

• 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.

Collaboration & Delivery

• 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.

Team Development

• 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.

Required Skills & Experience

• 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.

AI & Emerging Technology Experience

• 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.
  • Improving engineering productivity through AI tools.
• Curiosity and enthusiasm for adopting emerging technologies to improve software quality.

Preferred Qualifications

• Experience delivering enterprise SaaS applications.
• Experience within regulated industries such as EHS, ESG, Governance, Risk & Compliance, Audit, Legal, Finance, or Healthcare software.
• Experience testing complex cloud-based applications and distributed systems.
• Knowledge of cloud platforms such as Azure, AWS, or Google Cloud.
• Experience with performance, security, accessibility, or reliability testing.
• Familiarity with tools such as Jira, Azure DevOps, TestRail, Xray, or similar.
• Knowledge of the Tricentis tool suite (including Tosca and qTest) would be advantageous.
• 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.

What You'll Bring

• 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.

Our Interview Practices

To maintain a fair and genuine hiring process, we kindly ask that all candidates participate in interviews without the assistance of AI tools or external prompts. Our interview process is designed to assess your individual skills, experiences, and communication style. We value authenticity and want to ensure we’re getting to know you—not a digital assistant. To help maintain this integrity, we ask to remove virtual backgrounds and include in-person interviews in our hiring process. Please note that use of AI-generated responses or third-party support during interviews will be grounds for disqualification from the recruitment process.

Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.