Systems Platform QA and AI engineer

Overview

Drive quality engineering for enterprise storage platforms and develop AI/ML-enabled automation to improve system validation, debugging, test effectiveness, and engineering productivity.

What you'll do

• Drive end-to-end quality engineering for enterprise storage platforms, focusing on hardware-software interactions across hardware, firmware, BIOS, BMC/iLO, operating systems, kernel, device drivers, storage protocols, backend network, and platform software.
• Design and develop scalable automation frameworks and tools, primarily using Python, to improve test coverage, system validation, debugging, and productivity.
• Analyze interactions and dependencies between system layers in large-scale enterprise storage environments and ensure timely root cause analysis.
• Apply AI/ML-based approaches to failure analysis, test optimization, anomaly detection, workflow automation, and other complex engineering and quality problems.
• Build reusable tools and utilities that enhance engineering productivity, test effectiveness, and observability.
• Drive innovation and integration.
• Promote collaboration, continuous learning, and mentoring.

What you'll need

• 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.

Nice to have

• 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 applying AI/ML techniques to engineering or quality problems, including Gen AI/LLMs, prompt engineering, and AI-assisted testing.
• Strong problem-solving mindset with a QA/system thinking approach focused on reliability, scalability, and edge conditions.
• Excellent analytical and troubleshooting skills.
• Strong collaboration and communication skills.
• Proven ability and interest in mentoring and knowledge sharing.

Details

• The role is designated as Remote/Teleworker and primarily involves working from home.
• The job is based in Bengaluru, Karnataka, India.