Product Application Engineer - Data Center Deployment

Overview

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.

This highly technical role serves as a key technical engineer plus customer advisory level resource, responsible for the execution of data center cluster projects at AMD CSP partners and enterprise commercial end-customers. The position provides a unique opportunity to leverage expertise in systems management automation, graphics, compute, storage, networking, data center technologies, virtualization, AI/Machine Learning, and program management to collaborate with customers utilizing AMD Instinct™ Accelerators to build out large scale clusters.

You must be a team player with a strong commitment to meeting deadlines and the ability to thrive in a fast-paced, multi-tasking environment.

The ideal candidate possesses exceptional skills in AI GPU hardware, software, systems management, and networking, especially with high-speed data fabrics. This role also requires strong communication skills, with the ability to tactfully interface with both technical and program management resources at CSP and customer sites. Should be highly analytical, detail-oriented, self-motivated, and maintain a positive, results-driven attitude, as well as work closely with customers in an advisory role to provide guidance during large scale cluster bringup and validation.

The candidate should be a data center systems engineer, site reliability engineer lead, or platform engineer with experience in large scale system bringup, and a strong customer focus. Some familiarity with GPUs and machine learning techniques in an AI setting is a plus. They must be self-motivated and capable of working effectively within a team environment, as well as communicating concisely at all levels within an organization.

• Develop a strong understanding of the client’s business to assist with ensuring an impactful and effective task completion in bringup and validation of CSP and customer clusters.
• Provide technical guidance and support at an advisory level to customers for server clusters, focused on large scale GPU deployments.
• Build out datacenter GPU cluster environments for customer testing and deployment.
• Assist development teams in identifying and resolving hardware/software technical issues throughout the cluster lifecycle, from initial bring-up to entering service for running workloads.
• Provide technical guidance to internal teams based on customer feedback.
• Qualify and assess new cluster automation software functionality to ensure compatibility with customer requirements and datacenters.
• Resolve technical issues for customers utilizing AMD Instinct™ server products in clusters.
• Mentor junior members of the technical staff.
• Follow procedures to communicate, report, and escalate incidents to AMD management.
• Collaborate with program managers to maintain project schedules, track action items, ensure deliverables are met, and provide project status updates to customers and AMD management.

• Data center customer support hands-on management roles during cluster system bringup.
• Advisory PM and technical roles in large-scale data center cluster bringup.
• Data center customer support tool skills using automation tools and frameworks such as Ansible, bash, Python and others.
• Bringup of data center servers and racks, server architecture and functionality, including remote management via BMC, network topologies, and graphics software/hardware subsystems.
• Linux installation,…