Systems Platform QA and AI engineer

Jobgether SRL; India; Remote; INR 1,200,000 - 2,500,000; Full time

Benefits offered by this job

Remote work

Comprehensive benefits

Professional development

Inclusive workplace

Job summary

Jobgether SRL is seeking a Systems Platform QA and AI engineer in India to drive end-to-end quality engineering for enterprise storage platforms in a large-scale hybrid cloud environment.

The role involves Python automation, system validation across hardware, firmware, BIOS, and OS layers, and applying AI/ML techniques to optimize testing and reliability. This is a full-time remote role based in Bengaluru with opportunities to influence enterprise technology.

Qualifications

• 3-5 years of professional experience in enterprise storage or large-scale distributed systems.
• Strong Python programming skills with automation framework development.
• Solid understanding of software testing fundamentals and system validation.
• Good knowledge of Linux/Unix and debugging in complex environments.
• Experience applying AI/ML techniques to engineering or quality challenges preferred.

Responsibilities

• Drive end-to-end quality engineering for enterprise storage platforms across hardware, firmware, BIOS, and software layers.
• Design, develop, and maintain scalable Python-based automation frameworks and tools.
• Troubleshoot complex issues across system layers and dependencies in large-scale storage environments.
• Apply AI/ML techniques to failure analysis, test optimization, and anomaly detection.
• Build reusable tools to improve productivity, observability, and test coverage.
• Collaborate with cross-functional teams to resolve customer issues and improve reliability.
• Promote continuous learning, mentoring, and knowledge sharing across the team.

Skills

Python

Linux

Automation

AI/ML

Troubleshooting

Test automation

Systems thinking

Education

Bachelor's or Master's in CS/IS

Job description

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.

• 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.
• Design, develop, and maintain scalable automation frameworks and engineering tools, primarily using Python, to increase test coverage, validation effectiveness, debugging capabilities, and overall productivity.
• Troubleshoot complex issues across system layers and dependencies within large-scale enterprise storage environments, conducting root cause analysis and supporting timely resolution.
• 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.
• Build reusable tools and utilities that improve engineering productivity, test effectiveness, system observability, and the ability to diagnose complex platform behaviors.
• Collaborate with cross-functional engineering teams to resolve customer issues, improve system reliability, and address quality challenges throughout the development and validation lifecycle.
• Promote innovation, continuous learning, collaboration, mentoring, and knowledge sharing while contributing to improvements in engineering practices and quality processes.

Requirements

• Bachelor's or Master's degree in Computer Science, Information Systems, or an equivalent technical discipline.
• 3-5 years of professional experience, with strong exposure to enterprise storage systems or comparable large-scale distributed systems.
• Strong Python programming skills, including practical experience developing automation frameworks, tools, test systems, or engineering utilities.
• Solid understanding of software testing fundamentals, debugging methodologies, automation design, and system validation.
• Good knowledge of Linux/Unix operating systems and the ability to troubleshoot issues within complex technical environments.
• Demonstrated experience resolving customer issues, performing system-level debugging, and collaborating effectively with cross-functional engineering teams.
• Strong understanding of enterprise storage environments and their hardware, firmware, driver, and platform software layers is highly desirable.
• 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.
• Strong problem-solving and analytical skills, with a QA and systems-thinking mindset focused on reliability, scalability, edge cases, and root cause analysis.
• Excellent collaboration and communication skills, with the ability to explain technical issues clearly and work effectively with diverse engineering stakeholders.
• Demonstrated interest and ability in mentoring, knowledge sharing, and supporting continuous improvement across the team.

Benefits

• Remote/teleworker work arrangement, primarily working from home.
• Comprehensive benefits designed to support physical, financial, and emotional health and well-being.
• Access to personal and professional development programs supporting career growth and opportunities to deepen expertise or explore other areas.
• An inclusive workplace that values individual backgrounds, perspectives, and contributions.
• Opportunities to work on innovative enterprise cloud and storage technologies with complex engineering challenges.
• A collaborative environment that encourages continuous learning, mentoring, knowledge sharing, and innovation.
• Opportunities to develop expertise in AI/ML applications, automation, systems quality engineering, and large-scale enterprise platforms.