Senior Technical Support Engineer – Ethernet, AI Infrastructure

• Investigate and resolve complex issues involving NVIDIA Ethernet networking, Linux systems, servers, and large-scale AI infrastructure, including NVIDIA Spectrum-X end-to-end solutions.
• Own critical customer issues from initial response through resolution.
• Coordinate cross-functional teams and provide clear, timely communication to customers and leadership.
• Reproduce customer problems, analyze diagnostic data, identify root causes, and resolve installation, operation, maintenance, performance, and multivendor interoperability issues.
• Advise enterprise, cloud, and service-provider customers through telephone, email, and conference-based support engagements.
• Partner with Engineering and Product teams to translate field findings into product improvements, support tools, technical documentation, and troubleshooting methodologies.
• Provide technical leadership during high-severity incidents while managing priorities, risks, and customer expectations.
• Improve support effectiveness through automation, knowledge sharing, structured debugging practices, and agentic AI tools.

• 5+ years of experience providing in-depth technical support and debugging for networking, hardware, software, or enterprise infrastructure products.
• Deep knowledge of Ethernet and data center networking, including TCP/IP, Layer 2 and Layer 3 technologies, ARP, STP, LACP, MLAG, IGMP, PIM, BGP, OSPF, routing, and switching.
• Proven experience troubleshooting complex network issues using tcpdump, Wireshark, packet generators, telemetry, and log-analysis tools.
• Strong Linux system administration and networking skills, including diagnosing server, operating-system, driver, hardware, and performance issues.
• Excellent customer-facing, written, verbal, and presentation skills.
• Ability to explain complex technical issues, manage expectations, and build trust with customers and executives.
• Ability to lead high-severity customer situations, coordinate multiple technical teams, make sound decisions under pressure, and drive issues to timely resolution.
• Strong analytical, organizational, and prioritization skills; ability to work independently and manage multiple complex issues.
• Practical experience using agentic AI technologies such as Claude, Codex, or Cursor.
• Hands-on experience with AI infrastructure and at least two of: data centers, distributed systems, accelerated servers, virtualization, deep learning frameworks, Docker, Kubernetes, or high-performance computing.
• Bachelor’s or master’s degree in Computer Science, Computer Engineering, Electrical Engineering, Networking, or a related discipline, or equivalent practical experience.