Education: Bachelor's degree or related field
Experience: 4+ years
The RMA Engineer is responsible for managing and processing Return Material Authorizations (RMAs) for hyperscaler and enterprise server products. This role ensures timely evaluation, troubleshooting, and disposition of returned hardware, while collaborating with cross-functional teams to maintain product quality and customer satisfaction.
- Review and log all returned server components and systems.
- Maintain accurate RMA records and audit documentation for compliance.
- Track reasons for returns and generate reports for trend analysis.
- Perform root cause analysis and support corrective actions.
- Execute test plans for replacement parts and repaired units.
- Validate server SKUs and configurations for hyperscaler environments (AWS, Azure, GCP).
- Interface with engineering, supply chain, and customer support teams.
- Coordinate repair, upgrade, and return-to-service processes.
- Bachelor's degree in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 4+ years of Hardware Engineering or related work experience.
Master's degree in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 3+ years of Hardware Engineering or related work experience.
PhD in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 2+ years of Hardware Engineering or related work experience.
- Master's/Bachelor's degree in Electrical Engineering, Computer Engineering, or related field.
- 3-5 years in hardware troubleshooting or sustaining engineering.
- Familiarity with hyperscaler server hardware (CPU, memory, storage) and cloud platforms.
- Strong debugging and soldering skills (micro miniature preferred).
- Knowledge of server architecture, networking (TCP/IP, DNS), and hardware interfaces.
- Experience with automation tools (Ansible, Puppet) and scripting (Python, Bash).
- Excellent documentation, organizational, and communication skills.
- Ability to work cross-functionally and manage multiple priorities.
- Experienced in AI tools, including Microsoft Copilot, Claude, and Gemini.
- Experience with hyperscaler environments (AWS, Azure, GCP).
- Familiarity with server validation processes and performance tuning.
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