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AMD Logo AMD · IT - Software Development

Ai Solutions Architect / Field Application Engineer

United States, Austin 102320.00 - 153480.00 USD / Year · Job Posted March 25, 2026
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Job Description

We are looking for an AI enthusiast with strong technical fundamentals and customer-facing aptitude to join AMD as an Entry-Level 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
  • 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, including compute instance types and accelerators
  • Knowledge of containers and orchestration (Docker, Kubernetes)
  • Prior internship, co-op, or project experience in customer-facing or field engineering roles
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