Quality Analyst

SimplifyNext is a Singapore-headquartered digital engineering firm, with offices in Thailand and Malaysia, working across three converged areas: agentic AI, AI-enabled application modernisation, and intelligent automation. We bring strong business process consulting together with deep technology skills and modern delivery practices – product-centric, agile and AI-assisted. We build bespoke applications and AI systems, and we go deep on the platforms our clients run on, including Microsoft, AWS, ServiceNow, Databricks and UiPath. That combination of engineering depth and platform depth is what our clients come to us for. We build and modernise the systems people depend on daily. Our 300+ practitioners are multi-disciplinary by design – business consultants, software engineers, architects, AI engineers and designers working on the same delivery, not handing off between silos. We focus on delivering outcomes for clients, building strong careers for our people, and staying ahead of the technology curve. We hire because we are growing. At SimplifyNext, quality is not a phase – it is a discipline woven into every stage of how we deliver. As a Senior Quality Analyst, you will play a leadership role in shaping how quality is defined, engineered, and scaled across our engagements. You will work at the intersection of modern application development, AI-driven solutions, and enterprise automation, partnering with architects, engineers, and client stakeholders to ensure quality is built into the foundation – not tested at the end. This role goes beyond traditional QA. You will lead quality transformation for our clients, drive automation-first testing strategies, and explore how AI can redefine how quality is assured in complex, real-world systems. Responsibilities Quality Leadership & Strategy Define and lead end-to-end quality strategies for complex programmes, ensuring alignment with business outcomes, regulatory requirements, and modern architecture patterns. Act as a trusted advisor to clients and senior stakeholders, shaping how quality is approached across teams, platforms, and releases. Establish quality governance frameworks across multi-workstream programmes, including standards, metrics, and reporting structures. Shift-Left & Engineering Excellence Champion a shift-left and quality engineering mindset, embedding testing into design, development, and deployment practices. Partner with architects and developers to design for testability, ensuring systems are observable, resilient, and scalable. Advocate and guide teams on practices such as TDD, BDD, contract testing, and CI/CD-driven quality gates. Automation & AI-Driven Testing Lead the design and implementation of automation-first testing strategies across UI, API, data, and integration layers. Drive adoption of modern test automation frameworks such as Playwright, Cypress, and Selenium, and ensure they are scalable, maintainable, and integrated into delivery pipelines. Make informed decisions on tooling strategy (e.g. what to use for modern web apps vs legacy or cross-browser needs). Explore and implement AI-assisted testing approaches – including test generation, intelligent test selection, anomaly detection, and self-healing automation. Define approaches for testing AI/ML systems and agentic workflows, including handling non-deterministic behaviour, model drift, and data quality risks. End-to-End Quality Assurance Own quality across the full technology stack – from frontend experiences to backend services, integrations, and cloud infrastructure. Lead exploratory testing and risk-based validation, especially in complex, automation-heavy, or AI-driven solutions. <li data-leveltext="" data-font="Symbol" data-listid="6" data-list-defn-props="{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242"