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AMD · 5 days ago

Product Application Engineer- Datacenter Deployment

California, United States

Full-time

Hybrid

Mid, Senior Level

$188K/yr - $282K/yr

AMD is a company focused on building products that enhance next-generation computing experiences. The role involves supporting large-scale datacenter graphics hardware and software initiatives, collaborating with customer engineering teams to ensure successful deployment of solutions powered by high-performance accelerators.

AI InfrastructureArtificial Intelligence (AI)Cloud ComputingComputerEmbedded SystemsGPUHardwareSemiconductor

Growth Opportunities

No H1B

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 escalate 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

Qualification

Datacenter virtualizationDistributed systemsGPU-accelerated computeVirtualization technologiesNetworking environmentsLinux configurationAI/ML workloadsCommunication skillsProblem solvingInterpersonal skills

Required

Exceptional technical depth in datacenter virtualization, distributed systems, and ideally GPU-accelerated compute

Analytical, detail-oriented, proactive, and operate with a strong sense of ownership and urgency

Excel at troubleshooting across hardware, virtualization software, and networking stacks

Communicate complex concepts clearly

Build strong partnerships with customers

Self-starter who thrives in a collaborative engineering environment

Strong interpersonal skills

Maintain a positive, results-driven mindset