Systems Platform QA and AI Engineer
New
J
JobgetherEnterprise storage
Based in IndiaFull-TimeSenior
Salary not disclosed
Apply NowOpens the employer's application page
Job Details
- Experience
- 3–5 years of professional experience
- Required Skills
- PythonDistributed Systems
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.
- Knowledge of software testing fundamentals, debugging methodologies, automation design, and system validation.
- Good knowledge of Linux/Unix operating systems and the ability to troubleshoot complex technical environments.
- Experience resolving customer issues, performing system-level debugging, and collaborating with cross-functional engineering teams.
- Strong understanding of enterprise storage 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, or anomaly detection, 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.
- Ability to explain technical issues clearly and work effectively with engineering stakeholders.
- Interest and ability in mentoring, knowledge sharing, and supporting continuous improvement.
Responsibilities
- Validate interactions across hardware, firmware, BIOS, BMC/iLO, operating systems, kernels, device drivers, storage protocols, backend networks, and platform software.
- Design, develop, and maintain scalable Python automation frameworks and engineering tools.
- Troubleshoot complex issues across system layers and dependencies in enterprise storage environments.
- Conduct root cause analysis and support timely issue resolution.
- Apply AI and machine learning to failure analysis, test optimization, anomaly detection, workflow automation, generative AI, and AI-assisted testing.
- Build reusable tools and utilities that improve productivity, test effectiveness, observability, and diagnosis of platform behavior.
- Collaborate with cross-functional engineering teams to resolve customer issues and improve system reliability.
- Contribute to quality improvements throughout the development and validation lifecycle.
- Share knowledge, mentor others, and contribute to improvements in engineering practices and quality processes.
View Full Description & ApplyYou'll be redirected to the employer's site
