AMD—Product Application Engineer - Networking

Job description

Description: ADVANCE YOUR CAREER. ADVANCE THE WORLD. At AMD, we believe technology has the power to solve the world’s most important challenges. From advancing healthcare and scientific discovery to powering AI and the technologies people rely on every day, innovation at AMD is shaping the future. Whether you’re designing next-gen processors, enabling AI breakthroughs, or bringing leading edge products to market, every role at AMD contributes to something bigger — technology that moves the world forward. Join us and, together, we’ll advance your career. KEY RESPONSIBILITIES: - Support key customer and OEM engagements for current and next generation of AI networking and networking infrastructure products. - Collaborate across various teams in Engineering and Marketing to help resolve critical escalations. - Serve as a technical escalation point for complex, multi-layer issues spanning hardware, firmware, drivers, and software across AI infrastructure stacks. - Develop and deliver systems/product training to customers and contribute to the knowledge base for customer support and internal partners. - Be part of an on-call rotation to support production systems. - Develop and integrate AI-assisted workflows (e.g., LLM-based diagnostics, predictive failure analysis, agentic automation) into support operations and tooling. - Mentor junior engineers on technical approach, debugging methodology, and customer engagement best practices. - Drive process improvements and define best practices for support workflows based on recurring issue patterns and field data. PREFERRED EXPERIENCE: - Strong fundamentals in Datacenter Networking, Routing & Switching including load balancing (ECMP), underlay/overlay technologies, and network observability. - Strong fundamentals with the AI infrastructure stack — RDMA/RoCE, collective communication libraries (NCCL/RCCL), and distributed training and inference frameworks. - Understanding of AI cluster networking topologies, including rail-optimized and fat-tree designs for GPU-to-GPU communication. - Solid scripting and automation skills in Python, Go, or Shell. - Demonstrated ability to lead cross-functional troubleshooting efforts and drive resolution for critical, multi-team escalations. - Experience leading engagements with Hyperscalers, large enterprise, and OEM customers in a technical support role. - Familiarity with AI-powered tooling and automation (LLMs, AI agents, copilots) for engineering productivity and support operations. - Comfortable participating in and leading customer meetings, presenting technical findings, and translating complex issues into clear status updates for engineering leads and management. - Experience with software development processes and tools such as debuggers, profilers, and source code control systems (GitHub) is a plus. - Familiarity with DPU, SmartNIC, or InfiniBand protocol and RDMA bring-up and troubleshooting is a plus. #LI-NS2 Benefits offered are described: AMD benefits at a glance. AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process. AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here. This posting is for an existing vacancy. Responsibilities: KEY RESPONSIBILITIES: - Support key customer and OEM engagements for current and next generation of AI networking and networking infrastructure products. - Collaborate across various teams in Engineering and Marketing to help resolve critical escalations. - Serve as a technical escalation point for complex, multi-layer issues spanning hardware, firmware, drivers, and software across AI infrastructure stacks. - Develop and deliver systems/product training to customers and contribute to the knowledge base for customer support and internal partners. - Be part of an on-call rotation to support production systems. - Develop and integrate AI-assisted workflows (e.g., LLM-based diagnostics, predictive failure analysis, agentic automation) into support operations and tooling. - Mentor junior engineers on technical approach, debugging methodology, and customer engagement best practices. - Drive process improvements and define best practices for support workflows based on recurring issue patterns and field data. PREFERRED EXPERIENCE: - Strong fundamentals in Datacenter Networking, Routing & Switching including load balancing (ECMP), underlay/overlay technologies, and network observability. - Strong fundamentals with the AI infrastructure stack — RDMA/RoCE, collective communication libraries (NCCL/RCCL), and distributed training and inference frameworks. - Understanding of AI cluster networking topologies, including rail-optimized and fat-tree designs for GPU-to-GPU communication. - Solid scripting and automation skills in Python, Go, or Shell. - Demonstrated ability to lead cross-functional troubleshooting efforts and drive resolution for critical, multi-team escalations. - Experience leading engagements with Hyperscalers, large enterprise, and OEM customers in a technical support role. - Familiarity with AI-powered tooling and automation (LLMs, AI agents, copilots) for engineering productivity and support operations. - Comfortable participating in and leading customer meetings, presenting technical findings, and translating complex issues into clear status updates for engineering leads and management. - Experience with software development processes and tools such as debuggers, profilers, and source code control systems (GitHub) is a plus. - Familiarity with DPU, SmartNIC, or InfiniBand protocol and RDMA bring-up and troubleshooting is a plus. #LI-NS2