AI & Datacenter Solutions Architect

The Role 

We are looking for an ambitious, driven AI & Datacenter Solutions Architect with strong technical fundamentals and a proven customer-facing track record to join AMD. This is a frontline, tip-of-the-spear role where you will work closely with strategic datacenter, cloud, and emerging neocloud customers, internal engineering teams, and ecosystem partners to help deploy, optimize, and scale AI and high-performance workloads on AMD CPU and GPU platforms. 

This is not an entry-level position. We are looking for an experienced engineer who already knows how to earn a customer's confidence — someone with the energy and initiative to drive complex technical engagements from first conversation to production deployment. The role blends hands-on systems work, AI workload enablement, and technical program management. You will act as the technical bridge between field requirements and internal AMD teams, and your success will depend as much on how you build trust as on what you know. 

The Person 

Does this sound like you? We’d love to talk! 

• Experienced supporting customers in the compute and datacenter space — including cloud, on-prem, and the fast-growing neocloud providers — with the passion and drive to grow AMD’s footprint in demanding, high-stakes accounts 

• Able to communicate with persuasion and empathy — you meet customers where they are, listen first, and move conversations forward without losing the room 

• A natural at navigating and communicating across teams, aligning engineering, product, marketing, and sales around a shared customer outcome 

• Build trust and transparency by default; you are candid about what works, honest about what doesn’t, and reliable under pressure 

• Excellent problem-solving, time-management, prioritization, and organizational skills, able to lead complex problems involving multi-disciplined, multi-functional teams and many priorities at once 

• A standout colleague with excellent collaborative skills, able to work independently or as part of a team 

• Outstanding oral and written communication skills and demonstrated success in building strong technical relationships (internal: Sales, Marketing, Engineering; external: customers and OEMs) 

Key Responsibilities 

Customer & Field Engagement 

• Serve as the senior technical point of contact for strategic customers across cloud, on-prem, and neocloud (GPU-specialized cloud) providers, supporting AI and HPC workloads on AMD CPU and GPU platforms 

• Work directly with customer engineering and leadership contacts to understand their use cases, requirements, and constraints, and guide them through solution design and deployment 

• Deliver persuasive technical presentations, demos, and architecture walkthroughs to both technical and executive audiences, translating AMD’s differentiation into business value 

• Program-manage customer opportunities as they grow in complexity, coordinating activities across internal and external stakeholders and keeping momentum through long sales cycles 

Technical Enablement & Hands-On Work 

• Perform hands-on system bring-up including hardware installation, firmware configuration, OS installation, and driver setup 

• Deploy and validate open-source AI and HPC software stacks (e.g., Linux, ROCm, AI frameworks, containers) 

• Run functionality, performance, and scalability benchmarks on CPU and GPU workloads 

• Perform profiling and analysis of applications to identify performance bottlenecks and optimization opportunities 

• Support AI/agentic workloads spanning training, inference, and data preprocessing across CPU and GPU platforms 

Architecture & Platform Knowledge 

• Apply deep working knowledge of AMD CPU and GPU architectures and how they impact real-world workloads 

• Reason across full-stack solutions spanning hardware, system software, drivers, frameworks, and applications 

• Lead solution design for on-premises, cloud, neocloud, and hybrid deployments 

Cross-Functional Collaboration 

• Collaborate closely with engineering, product management, marketing, and sales teams to represent customer needs and navigate decisions across organizational boundaries 

• Provide structured voice-of-the-customer feedback to influence product features, documentation, and roadmap decisions 

• Contribute to internal knowledge sharing, best practices, and team initiatives, and mentor teammates where your expertise intersects their challenges 

Qualifications 

• Bachelor’s degree in Computer Science, Electrical Engineering, Computer Engineering, or a related field (or equivalent practical experience) 

• Demonstrated success in a customer-facing technical role supporting compute, datacenter, or cloud customers 

• Strong interest in AI/ML technologies and proven ability to work across hardware and software layers 

• Hands-on experience with Linux-based systems 

• Programming experience in one or more of: Python, C/C++, Bash 

• Familiarity with AI frameworks or tools (e.g., PyTorch, TensorFlow, ONNX, Hugging Face, or similar) 

• Strong communication skills with the ability to explain technical concepts clearly and persuasively 

• Ability to work effectively in a team-oriented, cross-functional environment 

Preferred Qualifications 

• Experience working with GPU computing and/or accelerator-based workloads 

• Exposure to profiling and performance analysis tools for CPU and GPU workloads 

• Understanding of computer architecture concepts (CPU pipelines, memory hierarchy, GPU execution models) 

• Experience setting up or working in a lab environment with servers, networking, and storage 

• Familiarity with cloud platforms such as AWS, Azure, Google Cloud, or Oracle Cloud — and/or neocloud GPU providers (e.g., CoreWeave, Lambda, Crusoe, Nebius) — including compute instance types and accelerators 

• Knowledge of containers and orchestration (Docker, Kubernetes) 

• Prior success in customer-facing or field engineering roles within the datacenter or cloud ecosystem 

What Success Looks Like in This Role 

• Customers successfully deploy and optimize AI and CPU/GPU workloads on AMD platforms with your support 

• You are recognized as a trusted technical advisor — internally and externally — because you consistently lead with transparency and follow through 

• You take on increasingly complex opportunities and grow AMD’s share of your customers’ addressable market 

• You actively contribute to a collaborative, high-performing team culture 

Location 

• This is primarily a work-from-home position open to candidates across the United States, outside the San Francisco Bay Area and Seattle metro areas 

• Willing to travel up to 25% for customer and lab engagements 

The Role 

We are looking for an ambitious, driven AI & Datacenter Solutions Architect with strong technical fundamentals and a proven customer-facing track record to join AMD. This is a frontline, tip-of-the-spear role where you will work closely with strategic datacenter, cloud, and emerging neocloud customers, internal engineering teams, and ecosystem partners to help deploy, optimize, and scale AI and high-performance workloads on AMD CPU and GPU platforms. 

This is not an entry-level position. We are looking for an experienced engineer who already knows how to earn a customer's confidence — someone with the energy and initiative to drive complex technical engagements from first conversation to production deployment. The role blends hands-on systems work, AI workload enablement, and technical program management. You will act as the technical bridge between field requirements and internal AMD teams, and your success will depend as much on how you build trust as on what you know. 

The Person 

Does this sound like you? We’d love to talk! 

• Experienced supporting customers in the compute and datacenter space — including cloud, on-prem, and the fast-growing neocloud providers — with the passion and drive to grow AMD’s footprint in demanding, high-stakes accounts 

• Able to communicate with persuasion and empathy — you meet customers where they are, listen first, and move conversations forward without losing the room 

• A natural at navigating and communicating across teams, aligning engineering, product, marketing, and sales around a shared customer outcome 

• Build trust and transparency by default; you are candid about what works, honest about what doesn’t, and reliable under pressure 

• Excellent problem-solving, time-management, prioritization, and organizational skills, able to lead complex problems involving multi-disciplined, multi-functional teams and many priorities at once 

• A standout colleague with excellent collaborative skills, able to work independently or as part of a team 

• Outstanding oral and written communication skills and demonstrated success in building strong technical relationships (internal: Sales, Marketing, Engineering; external: customers and OEMs) 

Key Responsibilities 

Customer & Field Engagement 

• Serve as the senior technical point of contact for strategic customers across cloud, on-prem, and neocloud (GPU-specialized cloud) providers, supporting AI and HPC workloads on AMD CPU and GPU platforms 

• Work directly with customer engineering and leadership contacts to understand their use cases, requirements, and constraints, and guide them through solution design and deployment 

• Deliver persuasive technical presentations, demos, and architecture walkthroughs to both technical and executive audiences, translating AMD’s differentiation into business value 

• Program-manage customer opportunities as they grow in complexity, coordinating activities across internal and external stakeholders and keeping momentum through long sales cycles 

Technical Enablement & Hands-On Work 

• Perform hands-on system bring-up including hardware installation, firmware configuration, OS installation, and driver setup 

• Deploy and validate open-source AI and HPC software stacks (e.g., Linux, ROCm, AI frameworks, containers) 

• Run functionality, performance, and scalability benchmarks on CPU and GPU workloads 

• Perform profiling and analysis of applications to identify performance bottlenecks and optimization opportunities 

• Support AI/agentic workloads spanning training, inference, and data preprocessing across CPU and GPU platforms 

Architecture & Platform Knowledge 

• Apply deep working knowledge of AMD CPU and GPU architectures and how they impact real-world workloads 

• Reason across full-stack solutions spanning hardware, system software, drivers, frameworks, and applications 

• Lead solution design for on-premises, cloud, neocloud, and hybrid deployments 

Cross-Functional Collaboration 

• Collaborate closely with engineering, product management, marketing, and sales teams to represent customer needs and navigate decisions across organizational boundaries 

• Provide structured voice-of-the-customer feedback to influence product features, documentation, and roadmap decisions 

• Contribute to internal knowledge sharing, best practices, and team initiatives, and mentor teammates where your expertise intersects their challenges 

Qualifications 

• Bachelor’s degree in Computer Science, Electrical Engineering, Computer Engineering, or a related field (or equivalent practical experience) 

• Demonstrated success in a customer-facing technical role supporting compute, datacenter, or cloud customers 

• Strong interest in AI/ML technologies and proven ability to work across hardware and software layers 

• Hands-on experience with Linux-based systems 

• Programming experience in one or more of: Python, C/C++, Bash 

• Familiarity with AI frameworks or tools (e.g., PyTorch, TensorFlow, ONNX, Hugging Face, or similar) 

• Strong communication skills with the ability to explain technical concepts clearly and persuasively 

• Ability to work effectively in a team-oriented, cross-functional environment 

Preferred Qualifications 

• Experience working with GPU computing and/or accelerator-based workloads 

• Exposure to profiling and performance analysis tools for CPU and GPU workloads 

• Understanding of computer architecture concepts (CPU pipelines, memory hierarchy, GPU execution models) 

• Experience setting up or working in a lab environment with servers, networking, and storage 

• Familiarity with cloud platforms such as AWS, Azure, Google Cloud, or Oracle Cloud — and/or neocloud GPU providers (e.g., CoreWeave, Lambda, Crusoe, Nebius) — including compute instance types and accelerators 

• Knowledge of containers and orchestration (Docker, Kubernetes) 

• Prior success in customer-facing or field engineering roles within the datacenter or cloud ecosystem 

What Success Looks Like in This Role 

• Customers successfully deploy and optimize AI and CPU/GPU workloads on AMD platforms with your support 

• You are recognized as a trusted technical advisor — internally and externally — because you consistently lead with transparency and follow through 

• You take on increasingly complex opportunities and grow AMD’s share of your customers’ addressable market 

• You actively contribute to a collaborative, high-performing team culture 

Location 

• This is primarily a work-from-home position open to candidates across the United States, outside the San Francisco Bay Area and Seattle metro areas 

• Willing to travel up to 25% for customer and lab engagements