Systems Platform QA and AI engineer
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Job Description
- Drives end-to-end quality engineering for enterprise storage platforms, with focus on hardware-software interactions (hardware, firmware, BIOS, BMC/iLO, operating systems, kernel, device drivers, storage protocols, backend network, and platform software).
- Designs and develops scalable automation frameworks and tools, primarily using Python, to improve test coverage, system validation, debugging, and productivity.
- Applies strong troubleshooting skills to analyze the interactions and dependencies between system layers in large-scale enterprise storage environments, ensuring timely root cause analysis. Incorporates AI/ML-based approaches to solve complex engineering and quality problems (e.g., failure analysis, test optimization, anomaly detection, and workflow automation). The interactions and dependencies between these layers in large-scale enterprise environments.
- Builds powerful, reusable tools and utilities that enhance engineering productivity, test effectiveness, and observability.
- Drives innovation and integration, promotes a culture of collaboration, continuous learning, and mentoring.