Senior Product Quality & Reliability Engineer (Npi, Manufacturing & AI-Enabled Quality)

We are seeking an experienced Senior Product Quality & Reliability Engineer to drive product and software quality across design, development, New Product Introduction, manufacturing and post-launch improvement activities. This is a technical, hands-on role covering hardware, software, electronics and manufacturing quality. You will work closely with Engineering, Manufacturing, Service, Supplier Quality and other global teams to identify risks early, improve product reliability and ensure successful product launches. You will establish and execute product quality strategies, lead risk-management and reliability activities, and apply quality engineering principles throughout the product lifecycle. You will also work with engineering, data and digital teams to identify opportunities where Artificial Intelligence, Machine Learning, analytics and automation can improve testing, defect detection, failure prediction and manufacturing productivity. The successful candidate will be passionate about moving quality earlier in the development lifecycle and building robust, scalable and sustainable quality processes. Key Responsibilities: 1.Product Quality and Reliability Develop and execute product and software quality strategies across New Product Introduction, continuation engineering, customer issues and improvement projects. Participate in design, architecture, code, drawing, specification, verification and validation reviews. Identify product, software, process and reliability risks early in the development lifecycle. Ensure products and software meet established standards for quality, reliability, usability, performance and manufacturability. Define and manage Critical-to-Quality characteristics and measurable quality requirements. Apply quality engineering methodologies such as APQP, Design for Six Sigma, Design for Reliability and FMEA. Prepare and present regular updates on product quality, reliability risks, corrective actions and project readiness. 2.Verification, Validation and Failure Analysis Develop and execute product verification, validation and reliability qualification plans. Plan, conduct and report reliability testing, including Highly Accelerated Life Testing and Ongoing Reliability Testing. Investigate product, module, software and reliability anomalies. Perform hands-on electrical, mechanical, system and manufacturing failure analysis. Lead Root Cause Failure Analysis and structured problem-solving activities. Drive corrective and preventive actions to resolve systemic product and process issues. Verify the effectiveness and sustainability of implemented corrective actions. 3.NPI and Manufacturing Quality Ensure product and manufacturing-process readiness for mass production. Drive quality planning and risk mitigation throughout New Product Introduction, product transfer and production ramp-up. Partner with Engineering, Manufacturing, Service and suppliers to improve product and process robustness. Review manufacturing assembly, testing, inspection and control processes. Identify quality trends, process variation and emerging manufacturing risks through data analysis. Support flawless product launches by ensuring appropriate quality controls, specifications, testing and escalation mechanisms are in place. Support the resolution of production, supplier and customer-quality issues. 4.AI, Analytics and Digital Quality Partner with data, engineering and digital teams to identify AI, analytics and automation opportunities across engineering, testing, quality and manufacturing workflows. Develop high-value use cases such as intelligent test optimisation, anomaly detection, predictive quality and failure-pattern recognition. Use engineering, manufacturing and test data to improve defect detection, test coverage, process capability and decision-making. Support the development of automated quality reports, dashboards and digital workflows. Convert quality and engineering challenges into scalable analytics and automation solutions. Support data validation, model validation and performance monitoring for AI-enabled quality solutions. Deliver measurable improvements in quality, productivity, test efficiency and risk prediction. 5.Quality Systems and Continuous Improvement Support the organisation’s Quality Management System and ISO 9001 requirements. Participate in or support internal, external, product and process audits. Review quality procedures, work instructions, control plans and supporting documentation. Le…