Systems Platform QA and AI engineer
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Job Description
Structured overview of role & requirementsAbout This Role
Lead end-to-end quality engineering for enterprise storage platforms focusing on hardware-software integration across multiple system layers.
Design and develop scalable Python-based automation frameworks and tools to enhance test coverage, system validation, debugging, and productivity.
Apply AI/ML approaches for failure analysis, test optimization, anomaly detection, and workflow automation to solve complex engineering and quality problems.
Minimum Requirements
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.
Strong programming skills in Python and solid understanding of testing fundamentals, debugging, and automation design.
Good understanding of Linux/Unix operating systems and demonstrated experience in customer issue resolution and system debugging.
Ideal Candidate Profile
Experienced in enterprise storage systems including hardware, firmware, drivers, and platform software layers.
Proficient in building automation frameworks, tools, and test systems using Python, with AI/ML application experience to engineering or quality challenges.
Strong problem-solving mindset with QA/system thinking focus on reliability, scalability, and edge conditions; capable of cross-functional collaboration and mentoring.