System Architect - Industrial Robotics and Healthcare

AMD; Austin (TX); On-site; USD 150,000 - 190,000; Full time

Job summary

AMD is seeking a technically accomplished System Architect to own architectures from concept to implementation within the Industrial, Robotics, and Healthcare unit. The role covers AI workloads, heterogeneous compute, FPGA and adaptive SoC platforms, ARM and x86, embedded software, and real-time control.

You will guide decisions, collaborate across teams, and support customers with measurable architecture guidance.

Qualifications

• Own system architecture documents and requirements.
• Experience with heterogeneous compute architectures including CPUs/GPUs/NPUs/FPGAs.
• Knowledge of FPGA and adaptive SoC architectures.
• Embedded systems development using C/C++, Python, Linux, Yocto/Buildroot.
• Experience with robotics and real-time control systems.
• Knowledge of industrial interfaces like EtherCAT, CAN-FD, SPI, I2C, PCIe, USB.
• Understanding safety/reliability standards such as IEC 61508, ISO 26262.

Responsibilities

• Define end-to-end system architectures for AI-enabled embedded and healthcare applications.
• Partition workloads across CPU, GPU, NPU, FPGA, AI Engines, MCUs, and external accelerators.
• Architect AI inference pipelines for vision, sensor processing, robotics, and edge intelligence.
• Develop system architecture specifications, data-flow diagrams, interface definitions, timing budgets, memory and bandwidth requirements.
• Partner with FPGA, software, firmware, AI, and system engineering teams to translate architecture concepts into executable designs.
• Review technical proposals and challenge assumptions using engineering analysis and measurable data.
• Support customer-facing technical discussions with clear system-architecture guidance.
• Guide proof-of-concepts, benchmarks, reference designs, and technical demonstrators.
• Identify system-level architectural risks early and recommend practical mitigation strategies.
• Ability to travel approximately 25% to support onsite customer meetings and engagements.

Skills

System architecture ownership

Heterogeneous compute

FPGA & adaptive SoC

ARM & x86 processors

Embedded software

Real-time control

Industrial interfaces

AI/edge inference

Clear architectural decisions

Education

Master's or PhD in Electrical/Computer Eng

Tools

C/C++

Python

Embedded Linux

Yocto

Buildroot

Device drivers

Job description

ADVANCE YOUR CAREER. ADVANCE THE WORLD. At AMD, we believe technology has the power to solve the world's most important challenges. From advancing healthcare and scientific discovery to powering AI and the technologies people rely on every day, innovation at AMD is shaping the future. Whether you're designing next-gen processors, enabling AI breakthroughs, or bringing leading edge products to market, every role at AMD contributes to something bigger - technology that moves the world forward. Join us and, together, we'll advance your career.

THE ROLE:

We are seeking a technically accomplished System Architect with proven experience owning system architecture from initial concept through implementation. This role will report to the Principal System Architect within the Industrial, Robotics, and Healthcare business unit. The successful candidate will define practical, scalable system architectures that can be implemented by customers and engineering teams. This position requires strong technical judgment across AI workloads, heterogeneous compute, FPGA and adaptive SoC platforms, ARM and x86 processors, embedded software, real-time control, sensors, communication interfaces, and safety-critical system considerations.

THE PERSON:

The ideal candidate is technically rigorous, implementation-focused, and comfortable working across AI, hardware, software, and system boundaries. You are able to simplify complex systems without compromising engineering accuracy and can clearly communicate architectural decisions, trade-offs, and recommendations to engineering teams, customers, and senior stakeholders. You should be comfortable challenging technical assumptions, identifying architectural risks early, and using measurable engineering criteria to guide system-level decisions.

KEY RESPONSIBILITIES:

• Define end-to-end system architectures for AI-enabled embedded, robotics, industrial, and healthcare applications.
• Partition workloads across CPU, GPU, NPU, FPGA programmable logic, AI Engines, MCUs, and external accelerators.
• Architect AI inference pipelines for vision, sensor processing, robotics, and edge intelligence applications.
• Evaluate architectural trade-offs involving latency, throughput, determinism, memory bandwidth, power, thermal constraints, functional safety, cost, and scalability.
• Develop system architecture specifications, data-flow diagrams, interface definitions, timing budgets, memory and bandwidth requirements, and implementation guidance.
• Partner with FPGA, software, firmware, AI, and system engineering teams to translate architecture concepts into executable designs.
• Review technical proposals and challenge assumptions using engineering analysis and measurable data.
• Support customer-facing technical discussions by providing clear and credible system architecture guidance.
• Guide proof-of-concepts, benchmarks, reference designs, and technical demonstrators.
• Identify system-level architectural risks early and recommend practical mitigation strategies.
• Ability to travel approximately 25% to support onsite customer meetings and engagements.

PREFERRED EXPERIENCE:

• Demonstrated experience owning system architecture documents, specifications, and system-level technical requirements.
• Strong understanding of heterogeneous compute architectures incorporating CPUs, GPUs, NPUs, FPGAs, embedded processors, MCUs, and dedicated accelerators.
• Practical knowledge of FPGA and adaptive SoC architectures and modern programmable logic design methodologies.
• Experience with embedded systems development using C/C++, Python, embedded Linux, device drivers, Yocto, Buildroot, or comparable environments.
• Experience with robotics and real-time control systems, including motor control, torque control, impedance control, multi-rate control loops, sensor acquisition, and deterministic scheduling.
• Knowledge of industrial and embedded interfaces such as EtherCAT, CAN-FD, CANopen, SPI, I²C, Ethernet, PCIe, MIPI, and USB.
• Understanding of system safety and reliability concepts, including watchdogs, safe states, diagnostics, fault detection, timeout handling, and applicable standards such as IEC 61508, ISO 26262, ISO 13849, and IEC 62304.
• Experience with AI and edge inference technologies.
• Familiarity with AI deployment frameworks and runtimes such as ONNX, PyTorch, TensorFlow, or comparable technologies.
• Knowledge and understanding of agentic AI concepts and architectures.
• Experience making hardware, software, and AI workload-partitioning decisions.
• Ability to define and analyze interface, timing, latency, bandwidth, and memory budgets.
• Experience conducting architecture trade-off analyses across multiple implementation options.
• Demonstrated ability to support engineering teams beyond the initial architecture and concept phases.
• Ability to explain architectural decisions using measurable technical criteria.

ACADEMIC CREDENTIALS:

Master's degree or PhD in Electrical/Electronic Engineering, Computer Engi