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Pearson • Madrid, Community of Madrid, Spain
Role & seniority: QA Lead (senior/lead role) focused on AI‑enhanced learning products
Stack/tools: QA strategy and processes; manual and automated testing (Playwright in TypeScript or Python); API testing (Postman/Newman or pytest + requests); CI integration; accessibility testing (WCAG 2.2); basic security testing (OWASP Top 10, ZAP); cloud fundamentals (Azure/AWS); Docker‑based test environments
Define and drive the overall QA strategy, standards, and lifecycle coverage across the product
Lead planning and execution of regression, accessibility, functional, performance, and AI‑specific testing; validate AI outputs and software behavior
Collaborate cross‑functionally (Product, Engineering, Data/AI/ML, UX, Operations, Support) to embed quality early and monitor quality metrics, risks, and process improvements
Proven QA leadership for AI‑driven, data‑intensive, or cloud‑based products
Strong Agile experience and continuous improvement mindset
Proficiency in Playwright (TypeScript or Python) with CI integration; Python for automation utilities; API testing (Postman/Newman or pytest + requests); accessibility testing (WCAG 2.2); security‑aware testing (OWASP Top 10, ZAP); cloud basics (Azure or AWS); Docker experience
Experience validating AI‑driven outputs and data integrity validation for AI systems
Deep familiarity with automated testing strategies, performance testing, and
Role aim The QA Lead ensures the reliability and quality of AI‑enhanced learning products by defining and executing the quality strategy, driving best‑in‑class testing practices, and working closely with engineering teams to deliver seamless and trustworthy user experiences.
Role profile The QA Lead is responsible for ensuring the quality, reliability, and compliance of both traditional software components and AI‑driven product features across the platform. This role plays a key part in validating system behaviour, safeguarding user experience, and elevating quality standards across the engineering organisation.
You will define the overall QA strategy, drive its adoption across teams, and actively contribute to hands‑on testing, automation, and validation. Working cross‑functionally, you ensure QA processes and standards are applied consistently throughout the development lifecycle.
Office Poland / Spain / UK
Responsibilities Define the overall QA strategy, standards, and processes across the product lifecycle. Guide and support engineering teams in adopting and executing QA practices effectively. Lead planning and execution of regression, accessibility, functional, performance, and AI‑specific testing across environments. Ensure the quality, reliability, and compliance of AI‑enhanced and traditional product features. Validate software behaviour and AI‑driven outputs to maintain a consistent and seamless user experience. Actively contribute to manual testing, automated testing (Playwright), and API validation efforts. Collaborate with Product, Engineering, Data, AI/ML, UX, Operations, and Customer Service to embed quality early in design and throughout delivery. Ensure alignment with security, compliance, and responsible AI requirements. Monitor key quality indicators, report risks, and use insights to optimise QA processes and testing effectiveness. Support data integrity validation for AI‑driven systems and features. Recommend improvements to processes, tools, and methodologies while staying up to date with industry best practices. Foster strong cross‑team collaboration, knowledge sharing, and contribute to a high‑quality, inclusive engineering culture.
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