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AMD · 2 weeks ago

Senior Director FDE – AI Software Development

San Jose, CA

Full-time

Onsite

Director/Executive

$279K/yr - $418K/yr

AMD is a company focused on building products that accelerate next-generation computing experiences. The Senior Director FDE – AI Software Development will lead the FDE organization, ensuring high-velocity customer outcomes and acting as the voice of the customer to translate challenges into engineering roadmaps.

AI InfrastructureArtificial Intelligence (AI)Cloud ComputingComputerEmbedded SystemsGPUHardwareSemiconductor

Growth Opportunities

No H1B

Responsibilities

Cluster Bring-up & Optimization: Oversee the technical onboarding of massive GPU clusters. Ensure your team can troubleshoot collective communication errors, debug framework issues, and optimize training/inference strategies

Utilization Engineering (The North Star Metric): Drive and maintain industry-leading Customer GPU Utilization across clusters of thousands of GPUs, making cluster satisfaction the key measure of success

High-Performance Model Deployment: Enable customer success by deeply optimizing open-sourced models (Llama 3, DeepSeek, Mixtral) and proprietary models for our specific hardware topology, utilizing tools like vLLM and TensorRT-LLM

Executive Technical Sponsorship: Act as the technical authority and executive sponsor on large deals, possessing the credibility to validate architecture with CTOs and VPs of AI

Feedback Loop: Aggressively channel field intelligence back to Product Engineering. If customers are struggling with a specific use case, then become the loudest voice in the room demanding a fix

Qualification

AI FrameworksDistributed ComputingGPU EcosystemTechnical LeadershipLLM OperationsCommercial AcumenHigh-Stakes Crisis ManagementVoice of the Customer

Required

Define and institutionalize the FDE Engagement Model to maximize resource leverage and ensure consistent, high-velocity customer outcomes

Serve as the Voice of the Customer internally: Translate field intelligence and customer challenges into concrete, prioritized engineering roadmaps, and ensure execution

Oversee the technical onboarding of massive GPU clusters

Ensure your team can troubleshoot collective communication errors, debug framework issues, and optimize training/inference strategies

Drive and maintain industry-leading Customer GPU Utilization across clusters of thousands of GPUs, making cluster satisfaction the key measure of success

Enable customer success by deeply optimizing open-sourced models (Llama 3, DeepSeek, Mixtral) and proprietary models for our specific hardware topology, utilizing tools like vLLM and TensorRT-LLM

Act as the technical authority and executive sponsor on large deals, possessing the credibility to validate architecture with CTOs and VPs of AI

Aggressively channel field intelligence back to Product Engineering

Demonstrated track record leading high-impact technical teams within high-stakes environments (e.g., Cloud Infrastructure, AI Platform, or HPC)

You understand the stack from the metal up

Deep understanding of commercial drivers (ARR, Churn, Margin) and the ability to articulate how technical solutions impact deal velocity and business outcomes

Experience leading through 'Sev0' customer incidents (e.g., massive training run failures), demonstrating the poise and clarity required to manage executive communication while guiding rapid root cause resolution

AI Frameworks: PyTorch, JAX, TensorFlow

Distributed Computing: Slurm, Ray, Kubernetes (K8s), Docker

GPU Ecosystem: NVIDIA drivers, CUDA profiling (Nsight Systems), Triton Inference Server

Significant experience with advanced LLM deployment and customization techniques, including fine-tuning (e.g., LoRA/QLoRA) and building RAG pipelines

BS, MS or equivalent with direct experience