Jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Systems Platform QA and AI engineer based in India.
This role drives end-to-end quality engineering for enterprise storage platforms within a large-scale hybrid cloud environment.
You will work across complex hardware and software layers, including firmware, BIOS, BMC/iLO, operating systems, drivers, storage protocols, and platform software.
The position combines advanced test automation, systems troubleshooting, and AI/ML techniques to solve challenging engineering and quality problems.
You will design scalable Python-based frameworks and reusable tools that improve validation, observability, productivity, and test coverage.
The role requires strong systems thinking and the ability to investigate dependencies across multiple technology layers.
You will contribute to innovation, continuous learning, collaboration, and knowledge sharing across engineering teams.
This is a full-time remote/teleworker opportunity based in Bengaluru, with meaningful scope to influence the reliability of enterprise technology.
Accountabilities
<ul>
<li>Drive end-to-end quality engineering for enterprise storage platforms, validating interactions between hardware, firmware, BIOS, BMC/iLO, operating systems, kernels, device drivers, storage protocols, backend networks, and platform software.</li>
<li>Design, develop, and maintain scalable automation frameworks and engineering tools, primarily using Python, to increase test coverage, validation effectiveness, debugging capabilities, and overall productivity.</li>
<li>Troubleshoot complex issues across system layers and dependencies within large-scale enterprise storage environments, conducting root cause analysis and supporting timely resolution.</li>
<li>Apply AI and machine learning approaches to engineering and quality challenges, including failure analysis, test optimization, anomaly detection, workflow automation, generative AI, and AI-assisted testing.</li>
<li>Build reusable tools and utilities that improve engineering productivity, test effectiveness, system observability, and the ability to diagnose complex platform behaviors.</li>
<li>Collaborate with cross-functional engineering teams to resolve customer issues, improve system reliability, and address quality challenges throughout the development and validation lifecycle.</li>
<li>Promote innovation, continuous learning, collaboration, mentoring, and knowledge sharing while contributing to improvements in engineering practices and quality processes.</li>
</ul>
Requirements
<ul>
<li>Bachelor’s or Master’s degree in Computer Science, Information Systems, or an equivalent technical discipline.</li>
<li>3–5 years of professional experience, with strong exposure to enterprise storage systems or comparable large-scale distributed systems.</li>
<li>Strong Python programming skills, including practical experience developing automation frameworks, tools, test systems, or engineering utilities.</li>
<li>Solid understanding of software testing fundamentals, debugging methodologies, automation design, and system validation.</li>
<li>Good knowledge of Linux/Unix operating systems and the ability to troubleshoot issues within complex technical environments.</li>
<li>Demonstrated experience resolving customer issues, performing system-level debugging, and collaborating effectively with cross-functional engineering teams.</li>
<li>Strong understanding of enterprise storage environments and their hardware, firmware, driver, and platform software layers is highly desirable.</li>
<li>Practical experience applying AI/ML techniques to engineering or quality challenges, including GenAI/LLMs, prompt engineering, AI-assisted testing, anomaly detection, or similar applications, is preferred.</li>
<li>Strong problem-solving and analytical skills, with a QA and systems-thinking mindset focused on reliability, scalability, edge cases, and root cause analysis.</li>
<li>Excellent collaboration and communication skills, with the ability to explain technical issues clearly and work effectively with diverse engineering stakeholders.</li>
<li>Demonstrated interest and ability in mentoring, knowledge sharing, and supporting continuous improvement across the team.</li>
</ul>
Benefits
<ul>
<li>Remote/teleworker work arrangement, primarily working from home.</li>
<li>Comprehensive benefits designed to support physical, financial, and emotional health and well-being.</li>
<li>Access to personal and professional development programs supporting career growth and opportunities to deepen expertise or explore other areas.</li>
<li>An inclusive workplace that values individual backgrounds, perspectives, and contributions.</li>
<li>Opportunities to work on innovative enterprise cloud and storage technologies with complex engineering challenges.</li>
<li>A collaborative environment that encourages continuous learning, mentoring, knowledge sharing, and innovation.</li>
<li>Opportunities to develop expertise in AI/ML applications, automation, systems quality engineering, and large-scale enterprise platforms.</li>
</ul>
How Jobgether Works
We use an
AI-powered matching process
to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice:
By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Systems Platform QA and AI engineer

Systems Platform QA and AI engineer

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