The Global Product & Service team is building a next-generation workflow and approval platform serving nearly 500,000 users and roughly 1,000 internal customers globally. Built on OutSystems Low-Code/No-Code and evolving toward AI-native, driven by automation, GenAI, and Agentic AI, the platform supports mission-critical business processes for a global corporation. This is not a short-term testing assignment but a long-term product transformation journey where quality engineering, intelligent automation, reliability, and customer trust are essential. The role combines roughly 70% hands-on quality engineering/automation/test strategy work with 30% leadership, coaching, and team capability building (up to 5 QA Engineers).

• Quality Strategy and Ownership: own and improve the end-to-end test/Quality Engineering strategy; establish risk-based testing, quality gates, and release criteria; ensure full coverage across functional, API, integration, regression, performance, security, accessibility, and production validation; drive shift-left/shift-right; make evidence-based go/no-go recommendations; track KPIs (automation coverage, defect leakage, regression duration, test stability, release confidence).

• Hands-On Automation Engineering: design, develop, and maintain scalable automation frameworks using Playwright with Python; build reliable automated tests for web apps, APIs, integrations, workflows, and critical business journeys; perform manual/exploratory testing when automation isn't sufficient; integrate automated tests into CI/CD; improve reusability, reporting, test data management, maintainability, and execution speed; reduce flaky tests and set coding/review standards for automation.

• Requirements and Product Testability: review requirements, designs, epics, user stories, and acceptance criteria; challenge ambiguity, identify risks, dependencies, edge cases, and negative scenarios early; improve testability, traceability, and Definition of Ready with Product Owner/BA; drive quality-by-design instead of testing only at the end.

• Integration and Non-Functional Quality: strengthen API, integration, business rule, permission, and approval workflow testing; plan and execute performance, load, stress, scalability, resilience, and recovery testing; collaborate with Architecture/DevOps/Security/Operations to ensure global platform reliability.

• AI-Driven Quality Engineering: apply AI to requirement analysis, test design, test data, automation, defect analysis, and regression optimization; explore Agentic AI for test generation, execution, monitoring, and continuous learning; ensure human review, traceability, security, and governance for AI-generated testing assets; measure AI value through coverage, productivity, defect detection, and cycle time.

• Team Leadership and Collaboration: lead, mentor, and develop up to 5 QA Engineers; build a collaborative, accountable, high-performing Quality Engineering culture; provide technical direction, coaching, feedback, and fair work distribution; grow team capability in automation, product knowledge, and AI; collaborate with Product/Engineering/Architecture/DevOps/UX/Operations/Support; lead root-cause analysis and systemic preventive actions.

• Quality Monitoring and Reporting: monitor test execution, defects, automation health, release risk, and production quality; build clear dashboards and executive-level reporting; turn quality data into concrete insights, actions, and recommendations.