1215799 Systems Platform QA and AI engineer

Lead end-to-end quality engineering for enterprise storage platforms focusing on multi-layer hardware-software interactions including firmware, BIOS, operating systems, and drivers.

Design and develop scalable Python automation frameworks to enhance test coverage, system validation, and debugging across large-scale storage environments.

Incorporate AI/ML techniques to address complex quality challenges such as failure analysis, test optimization, anomaly detection, and workflow automation.

Bachelor's or Master's degree in Computer Science, Information Systems, or equivalent.

3-5 years of experience with strong exposure to enterprise storage systems or similar large-scale distributed systems.

Proficiency in Python programming and solid understanding of Linux/Unix operating systems and testing fundamentals.

Experience in system debugging, customer issue resolution, and collaboration across engineering teams.

Experience working on large-scale enterprise storage or distributed systems with a focus on hardware-software integration layers.

Strong background in building automation frameworks and applying AI/ML-driven solutions to enhance quality assurance processes.

Ability to perform root cause analysis and troubleshoot complex interactions across multiple system layers in an enterprise environment.