Product Application Engineer- Data Center Deployment

WHAT YOU DO AT AMD CHANGES EVERYTHING

At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career. The Role This highly technical role supports large-scale datacenter graphics hardware and software subsystem initiatives for cloud service provider and enterprise customers. You will work across complex virtualization, networking, datacenter infrastructure, AI/Machine Learning, and system-level program execution to ensure customers can successfully deploy solutions powered by high-performance accelerators. You will collaborate closely with customer engineering teams on system readiness, deployment, performance validation, and issue resolution. This role is ideal for someone who enjoys hands‑on datacenter networking work, solving complex distributed computing problems, and influencing customer success for next-generation GPU and CPU technologies. The environment is fast-paced, highly cross‑functional, and technical in nature. The Person You bring exceptional technical depth in datacenter virtualization, distributed systems, and ideally GPU-accelerated compute. You are analytical, detail-oriented, proactive, and operate with a strong sense of ownership and urgency. You excel at troubleshooting across hardware, virtualization software, and networking stacks, communicating complex concepts clearly, and building strong partnerships with customers. You are a self-starter who thrives in a collaborative engineering environment, brings strong interpersonal skills, and maintains a positive, results‑driven mindset. Key Responsibilities Design, optimize, and troubleshoot virtualization solutions for high-performance datacenter GPU, CPU, and related platforms. Support customers, partners, and internal teams on virtualization topics related to AI and Machine Learning workloads. Work with virtualization technologies across multiple vendors such as KVM, Kubernetes, VMware, and Hyper‑V. Build and configure datacenter networking environments for customer testing, validation, and deployment. Qualify and assess new virtualization capabilities to ensure alignment with customer and product requirements. Provide mentorship and technical guidance to junior engineering staff. Partner with development teams to identify and resolve hardware/software issues from early bring‑up through end‑of‑life. Document and elevate technical issues following established procedures. Collaborate with program managers to maintain schedules, track action items, and ensure deliverables are met. Provide clear project status updates to internal leadership and customer stakeholders. Build a deep understanding of customer goals to ensure impactful technical guidance and solution delivery. Translate customer feedback into actionable recommendations for internal engineering teams. Travel up to 20% to support customer deployments, onsite debugging, technical reviews, and collaborative engineering sessions. Preferred Experience Datacenter customer support in virtualization-focused environments. Virtual environments (VMware, Citrix, KVM, Microsoft, and others) and virtual machine configuration/management. Data storage, protection, deduplication, and storage-related network optimization especially with Weka, DDN, and VAST products. Working in or closely with a deployment services organization utilizing tools like Salesforce, JIRA and Confluence. Linux installation, configuration, debugging, and performance tuning. Debugging, root‑cause analysis, and system-level problem solving. Site reliability engineering concepts and best practices. Server architecture, remote management, network topologies, and compute subsystem operations. Datacenter GPU software stacks such as ROCm™ or CUDA. High‑performance networks for HPC and AI (RDMA/RoCE, InfiniBand). AI/ML workloads, frameworks, and models. Strong verbal and written communication skills to convey highly technical concepts. Ability to operate independently, manage multiple priorities, and maintain strong organizational discipline. Academic Credentials Bachelor’s or Master’s degree in Engineering, Computer Science, or related field preferred. Certifications Certifications preferred, including Kubernetes, VMware, Citrix, RedHat, KVM, Hyper‑V and others related to Networking, Virtualization, or Data Storage. Location: Austin, TX, Santa Clara, CA, Secaucus, NJ or Markham, Canada This role is not eligible for visa sponsorship. 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. #J-18808-Ljbffr AMD