QA Engineer [Public Healthcare]

• 10-month contract, renewable • Government project • Hybrid work arrangement Project OverviewAs the platform expands beyond specialist settings into general psychiatry and care coordination workflows, it has demonstrated both clinical value and the need for greater scalability, flexibility across care models, and stronger system integration to support higher patient volumes and broader population use. In response, the platform is evolving from a single clinical product into a scalable, modular digital phenotyping platform. This platform adopts a layered approach to user engagement and data collection, ranging from low-touch, privacy-first mobile engagement with minimal data collection, to opt-in digital phenotyping using smartphone and wearable data, and up to fully integrated, clinician-supported care models. This tiered design enables safe, large-scale adoption at lower layers while preserving clinical rigour and validated use in higher-acuity settings. It also supports Bring Your Own Device (BYOD) models and lightweight mobile-only implementations, improving accessibility and cost efficiency. A key feature of this platformisation is the ability to dynamically adjust a user's level of participation based on clinical need, risk signals, and user consent—enabling seamless transitions between self-guided and clinician-supported care. Supported by ongoing efforts such as Healthcare Commercial Cloud (HCC) migration and integration with platforms, the platform is positioning itself as a foundational, privacy-first digital phenotyping service that can power multiple mental health use cases across MOH, from population wellbeing to high-acuity clinical care. Responsibilities• Ensure that all components—from data ingestion to user- and clinician-facing insights—meet high standards of accuracy, safety, compliance, and user experience across layers L1–L4 • Create test plans for end-to-end data journeys, from sensor capture to insights surfaced in apps or clinician dashboards • Implement automated testing using Python, SQL, Appium, Playwright, and other relevant tools • Test guardrails to ensure no diagnostic language, no unsafe claims, and correct labeling of uncertainty • Perform device variability and BYOD acceptance testing (e.g., cross-device sleep metrics, heart-rate fidelity, sampling frequency differences) • Validate permissions, consent flows, pause/withdraw actions, and data minimization logic • Conduct regression tests for pipeline changes that could affect clinical summaries or user-facing narratives • Collaborate with Data and DevOps engineers to implement automated QA in CI/CD pipelines (e.g., synthetic data, replay tests, chaos testing for data dropouts) Requirements• Bachelor’s degree in Computer Science, Software Engineering, or a related field • Minimum 4 years of experience in software quality assurance or testing roles • Experience in automated testing using tools such as Python, SQL, Appium, Playwright, or similar • Familiarity with testing data pipelines, APIs, and end-to-end system workflows • Understanding of CI/CD practices and experience integrating QA into automated pipelines • Experience with mobile application testing, including cross-device and BYOD scenarios, is an advantage • Strong attention to detail, especially in validating data accuracy, edge cases, and user-facing outputs • Good communication skills and ability to collaborate with cross-functional teams (e.g., Data, Engineering, DevOps)