1215799 Systems Platform QA and AI engineer

In the HPE Hybrid Cloud, we lead the innovation agenda and technology roadmap for all of HPE. This includes managing the design, development, and product portfolio of our next-generation cloud platform, Green Lake. Working with customers, we help them reimagine their information technology needs to deliver a simple, consumable solution that helps them drive their business results. Join us redefine what’s next for you.

• →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.

• 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.
• Solid understanding of testing fundamentals, debugging, and automation design.
• Good understanding of Linux/Unix operating systems.
• Demonstrated experience in customer issue resolution, system debugging, and cross-functional engineering collaboration.

• Expertise in enterprise storage systems, including hardware, firmware, drivers, and platform software layers.
• Proficiency in Python programming with proven experience in building automation frameworks, tools, and test systems.
• Experience in applying AI/ML techniques to engineering or quality problems (e.g., Gen AI / LLMs, prompt engineering, AI-assisted testing).
• Strong problem-solving mindset with a QA/system thinking approach, focusing on reliability, scalability, and edge conditions.
• Excellent analytical and troubleshooting skills. Strong collaboration and communication skills. Proven ability and interest in mentoring, knowledge sharing.

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