Job description

WHAT YOU DO AT AMD CHANGES EVERYTHING At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career. THE ROLE: AMD is seeking a Principal AI Software & Systems Architect to help drive adoption of AMD AI solutions in the on premise, enterprise environment. This role requires deep expertise in AI software stacks, inference runtimes, heterogeneous computing, and hardware-aware software architecture. You will analyze real-world AI deployments, determine how workloads should be mapped across CPUs, GPUs, NPUs, and distributed infrastructure, identify platform and ecosystem gaps, and drive the technical work required to enable successful enterprise deployments on AMD platforms. The ideal candidate can reason about AI workloads from framework to hardware and translate customer requirements into software, platform, and product direction. THE PERSON: The ideal candidate is a systems-oriented software architect with deep understanding of AI frameworks, accelerators, and performance engineering. You are comfortable taking a customer deployment built for another platform, determine what parts run unchanged, what parts must be modified, what parts are missing from the ecosystem, and what engineering investments are required to make the workload successful on AMD. You bring: • Deep understanding of AI workload architecture and hardware-aware software design • Experience analyzing complex software stacks spanning frameworks, runtimes, drivers, operating systems, and hardware • The ability to move seamlessly between architecture, performance analysis, and technical execution • Strong customer and ISV engagement skills with engineering-level credibility • The ability to influence software, hardware, and product roadmaps using real-world workload requirements KEY RESPONSIBILITIES AI Workload Analysis & Architecture • Analyze customer and ISV AI deployments, including models, frameworks, runtimes, serving infrastructure, and dependencies. • Decompose workloads to identify portability, performance, scalability, and operational requirements. • Determine the optimal deployment architecture across client, edge, workstation, and datacenter environments. • Evaluate how workloads should be partitioned across CPUs, GPUs, NPUs, and distributed compute resources for optimal performance and overall TCO, including modeling of the TCO for customers. • Define reference architectures for enterprise AI deployments and emerging AI workload patterns. Platform Enablement & Optimization • Identify software, runtime, framework, compiler, driver, and hardware dependencies that impact deployment on AMD platforms. • Define and drive the technical work required to enable workloads on AMD hardware and software stacks. • Partner with engineering teams to close ecosystem gaps, improve platform readiness, and accelerate customer adoption. • Analyze workload performance and identify bottlenecks related to compute, memory, communication, storage, power, and utilization. • Establish performance targets, validation criteria, and benchmarking methodologies to support TCO discussions. Customer & ISV Technical Leadership • Serve as the technical lead for strategic customer and ISV engagements. • Conduct architecture reviews and technical assessments of AI deployments. • Guide customers and partners through workload migration, platform selection, enablement, and optimization activities. • Develop reusable deployment patterns, best practices, and technical guidance that can be applied across multiple engagements. Product & Platform Strategy • Translate real-world workload requirements into software, platform, and hardware requirements. • Influence AMD roadmap priorities through direct engagement with customers, ISVs, and ecosystem partners. • Identify emerging AI deployment trends and opportunities across client, edge, workstation, and datacenter markets. • Help shape AMD's long-term AI platform strategy through workload-driven insights and technical leadership. PREFERRED QUALIFICATIONS • Deep understanding of AI inference systems, model serving architectures, AI infrastructure, and performance optimization in production environments. • Strong understanding of AI software stacks, including frameworks, runtimes, compilers, drivers, and accelerator libraries. • Experience analyzing and optimizing software across multiple layers of the stack, from application and framework behavior through runtime, operating system, driver, and hardware interactions. • Strong understanding of heterogeneous computing architectures and workload partitioning across CPUs, GPUs, NPUs, and distributed compute resources. • Experience evaluating workload characteristics such as latency, throughput, memory footprint, communication patterns, scalability, power efficiency, and total cost of ownership (TCO). • Experience enabling, optimizing, porting, or debugging software on GPU or other accelerator platforms. • Ability to decompose complex customer deployments, identify software and platform dependencies, and define the technical work required to achieve successful deployment on a new platform. • Experience leading technical discussions with customers, ISVs, and internal engineering teams. ACADEMIC CREDENTIALS: • Bachelor’s or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent LOCATIONS: Austin, TX. Boxborough, MA. Markham, Ontario, CA. This role is not eligible for visa sponsorship. #LI-CB1 Benefits offered are described: AMD benefits at a glance . AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process. AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here. This posting is for an existing vacancy.

Requirements

Must-haves

Deep understanding of AI workload architecture and hardware-aware software design
Experience analyzing complex software stacks spanning frameworks, runtimes, drivers, operating systems, and hardware
The ability to move seamlessly between architecture, performance analysis, and technical execution
Strong customer and ISV engagement skills with engineering-level credibility
The ability to influence software, hardware, and product roadmaps using real-world workload requirements
AI Workload Analysis & Architecture
Analyze customer and ISV AI deployments, including models, frameworks, runtimes, serving infrastructure, and dependencies.
Decompose workloads to identify portability, performance, scalability, and operational requirements.
Determine the optimal deployment architecture across client, edge, workstation, and datacenter environments.
Evaluate how workloads should be partitioned across CPUs, GPUs, NPUs, and distributed compute resources for optimal performance and overall TCO, including modeling of the TCO for customers.
Define reference architectures for enterprise AI deployments and emerging AI workload patterns.
Platform Enablement & Optimization
Identify software, runtime, framework, compiler, driver, and hardware dependencies that impact deployment on AMD platforms.
Define and drive the technical work required to enable workloads on AMD hardware and software stacks.
Partner with engineering teams to close ecosystem gaps, improve platform readiness, and accelerate customer adoption.
Analyze workload performance and identify bottlenecks related to compute, memory, communication, storage, power, and utilization.
Establish performance targets, validation criteria, and benchmarking methodologies to support TCO discussions.

Nice-to-haves

Deep understanding of AI inference systems, model serving architectures, AI infrastructure, and performance optimization in production environments.
Strong understanding of AI software stacks, including frameworks, runtimes, compilers, drivers, and accelerator libraries.
Experience analyzing and optimizing software across multiple layers of the stack, from application and framework behavior through runtime, operating system, driver, and hardware interactions.
Strong understanding of heterogeneous computing architectures and workload partitioning across CPUs, GPUs, NPUs, and distributed compute resources.
Experience evaluating workload characteristics such as latency, throughput, memory footprint, communication patterns, scalability, power efficiency, and total cost of ownership (TCO).
Experience enabling, optimizing, porting, or debugging software on GPU or other accelerator platforms.
Experience leading technical discussions with customers, ISVs, and internal engineering teams.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

Platform: amd
Effort: medium