Lead end-to-end validation efforts for platform services with emphasis on reliability, scalability, upgradeability, customer experience, and production readiness Works with appropriate stakeholders to influence architecture and design decisions, establish quality standards, drive release readiness reviews, and continuously improve product quality through customer feedback, telemetry, and live-site learnings Acts as a Designated Responsible Individual (DRI) working on-call to monitor system/product feature/service for degradation, downtime, or interruptions and gains approval to restore system/product/service for simple problems Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python Master's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience Validating cloud-native platforms, Kubernetes-based solutions, distributed systems, and infrastructure services at scale Large-scale cloud services, distributed systems, or infrastructure platforms serving enterprise or hyperscale customers Defining release governance, quality metrics, test coverage strategies, and production readiness reviews for complex platform products Service operations, live-site practices, incident management, telemetry-driven quality improvements, and customer issue analysis Mentoring engineers and driving quality engineering best practices across teams or organisations Defining and driving quality strategy, test architecture, validation methodologies, and release readiness processes for large-scale distributed systems, cloud platforms, or enterprise software products Kubernetes storage ecosystems, CSI architecture, stateful workloads, persistent storage concepts, and storage lifecycle management, including provisioning, expansion, snapshots, cloning, backup/restore, upgrades, and operational workflows Storage platform fundamentals, including availability, resiliency, disaster recovery, scalability, capacity management, performance, and operational excellence Leveraging AI-assisted engineering tools to improve software quality, test effectiveness, or engineering productivity Partnering closely with Software Engineers, Product Managers, and partner teams to drive quality outcomes throughout the software development lifecycle Leading end-to-end validation efforts for platform services with emphasis on reliability, scalability, upgradeability, customer experience, and production readiness Working knowledge of automation and test infrastructure design to improve validation efficiency and coverage Demonstrated ability to identify quality risks early, influence architecture and design decisions, and establish quality standards across engineering teams
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