Platform Quality Engineer

AI Digital is reshaping the future of programmatic media through Elevate, our proprietary AI-powered platform designed to enable smarter marketing research, media planning and ad campaign optimization. We’re looking for a Platform Quality Engineer (Technical Support & QA Specialist) to join our team and act as a key link between Support, Product and Engineering. This is a hybrid role combining hands-on QA within our release cycle with second-line technical support and in-depth investigation of platform and reporting issues. You’ll help identify and resolve issues before they reach our clients, while also taking ownership of complex technical queries and ensuring effective collaboration across teams. Responsibilities: Ensure that new features and updates do not introduce regressions or impact existing platform functionality, enabling smooth and reliable releases. Execute comprehensive QA and regression testing for every release of Elevate across both development and production environments. Identify, document and communicate issues through clear, precise, and reproducible bug reports, including expected versus actual platform behavior. Develop and continuously improve test cases, regression checklists, and known-issue documentation to make each release more efficient and consistent. Own second-line technical support for Elevate across both external and internal users. Manage technical escalations from the first-line Support team, translate incoming requests into clear and actionable requirements, and drive issues through to resolution. Investigate complex technical issues end-to-end, including dashboard preparation problems, unexpected platform behavior, data discrepancies, integration failures, and other issues affecting platform functionality or reporting. Provide technical support to operational teams during migrations, implementations, and rollouts of new solutions, ensuring a smooth transition and timely resolution of technical challenges. Review client-facing dashboards and reporting outputs, identify data discrepancies and UI/UX inconsistencies, determine the most effective path to resolution, and coordinate with relevant teams to ensure issues are addressed.