• Define and drive the AI Enablement strategy for QA, taking the initiative, owning projects that scale, and introducing new capabilities to both QA and Engineering • Architect, build, and improve existing quality automation frameworks such as our current Playwright stack. Identify opportunities and roadmap the future of our automation. • Own the automated collection of QA metrics and operationalize the data to drive business outcomes. Identify and attribute trends in quality data and socialize learnings. • Lean in directly with our most critical projects to provide urgent, net-new, or enhanced automated coverage, particularly in domains that currently have gaps today • Contribute to coding standards and software engineering best practices, improving the quality of code written by both people and AI agents at scale • Facilitate the expansion of the QA team's capabilities into new domains, such as data, performance, and stability. • Own and improve the quality-related components of our release process, taking direct responsibility for the QA CI Strategy. Specifically, contribute to improved Cycle Time and Deployment rate without compromising quality metrics. • Mentor our QAs towards increasingly AI-enabled and automation-first ways of working

• Validar la funcionalidad del usuario final en escritorios NDS.Next • Realizar pruebas de aplicaciones, reproducción de defectos y pruebas de regresión antes y después de la migración • Solucionar y resolver problemas en Windows, aplicaciones y configuraciones de entorno de escritorio • Redactar actualizaciones de usuario claras y notas técnicas; gestionar expectativas y cerrar problemas • Proporcionar informes estructurados sobre carga de trabajo asignada

• Design and implement E2E test automation using Playwright, Cypress, or equivalent • Build API integration test suites for RESTful endpoints (OData V3 pattern) • Create and maintain CI/CD test pipeline integration—automated tests run on every PR • Develop multi-tenant isolation test suites to verify data security across portals • Build performance test baselines for critical operations (availability queries, conflict detection) • Use AI coding assistants daily to accelerate test creation, data generation, and maintenance • Collaborate with developers to establish testable patterns in application code • Define test data management strategies for development and staging environments • Own quality metrics—coverage, defect escape rate, regression pass rate • Participate in code reviews with focus on testability and edge case coverage

• Coordinate and execute software deployments across multiple environments (staging, testing, production) • Collaborate with development and operations teams to plan and schedule deployment activities • Implement and maintain Continuous Integration/Continuous Deployment (CI/CD) pipelines • Monitor and troubleshoot deployment processes to ensure smooth execution and timely delivery. Address and resolve any issues or failures in deployment processes • Automate deployment tasks where possible to reduce manual intervention and increase efficiency • Ensure version control and proper documentation of deployment procedures and configurations • Perform post-deployment testing to ensure functionality and performance are as expected • Maintain and update deployment tools and scripts to improve reliability and automation • Provide support to the development team in testing, validating, and deploying application changes • Work with cloud platforms (AWS, Azure, GCP, OCI) to manage deployments and configurations • Ensure compliance with security and operational standards during deployments • Provide regular status updates on deployment progress and potential risks to stakeholders