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We are looking for an AI enthusiast with strong technical fundamentals and customer-facing aptitude to join AMD as an AI Solutions Architect / Field Application Engineer. This is a frontline, tip-of-the-spear role where you will work closely with 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 role blends hands-on systems work, AI workload enablement, and technical program management. You will help customers move from early exploration through proof-of-concept and into production, while acting as a technical bridge between field requirements and internal AMD teams.
Job Responsibility:
Serve as a technical point of contact for customers, supporting AI and HPC workloads on AMD CPU and GPU platforms
Work directly with customers to understand their use cases, requirements, and constraints, and guide them through solution design and deployment
Deliver technical presentations, demos, and architecture walkthroughs to both technical and non-technical audiences
Program-manage customer opportunities as they grow in complexity, coordinating activities across internal and external stakeholders
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 first-level profiling and analysis of applications to identify performance bottlenecks and optimization opportunities
Support AI workloads such as training, inference, and data preprocessing across CPU and GPU platforms
Develop working knowledge of AMD CPU and GPU architectures and how they impact real-world workloads
Understand full-stack solutions spanning hardware, system software, drivers, frameworks, and applications
Assist in solution design for on-premises, cloud, and hybrid deployments
Collaborate closely with engineering, product management, marketing, and sales teams to represent customer needs
Provide structured feedback from the field to help influence product features, documentation, and roadmap decisions
Contribute to internal knowledge sharing, best practices, and team initiatives
Requirements:
Bachelor’s degree in Computer Science, Electrical Engineering, Computer Engineering, or a related field (or equivalent practical experience)
Strong interest in AI/ML technologies and a desire to work across hardware and software layers
Hands-on experience with Linux-based systems
Programming experience in one or more of the following: 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
Ability to work effectively in a team-oriented, cross-functional environment
Nice to have:
Experience working with GPU computing and/or accelerator-based workloads
Exposure to profiling and performance analysis tools for CPU and GPU workloads