Director Software System Design / AI System Performance

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

We are seeking a senior engineering leader for the AI System Performance, RAs Customer CoEngineering and System Deployment to lead deep, technical customer engagements that enable successful deployment of AI on edge and physical AI platforms at the system level.

THE PERSON

This role owns the endtoend lighthouse customer AI deployment journey-from early singlemodel evaluation, experience and performance optimization, through multimodel, concurrent, multitenant system deployment, integrated with marketspecific workloads such as robotics control, digital cockpit graphics, realtime perception, and safetycritical systems. Taking those learning from these strategic customer deployments to create right reference architectures demonstrating most important system performance metrics to scale the business.

You will lead and grow a senior, multidisciplinary coengineering organization that bridges AI models, toolchains and runtimes, system-software and segment SDKs, sensor and media pipelines, and silicon, ensuring light-house customers adopt AMD solutions and execute smoothly from proofofconcept to scalable, productiongrade systems.

This is a technical leadership role, focused on critical reference architectures enabling real scalable deployments-not just demos or POCs. deploying multiple models, concurrently, at scale, within real embedded systems is challenging problem. This role ensures AI succeeds in real products, under real constraints, across robotics, digital cockpit, and physical AI deployments.

KEY RESPONSIBILITIES:

Customer AI Deployment Leadership

• Own seniorlevel technical relationships with strategic AI customers across Robotics, Digital Cockpit, Industrial, Automotive, and Edge/Physical AI markets
• Serve as the senior technical authority guiding customers through the full AI deployment lifecycle:
• Singlemodel bringup and correctness validation
• Modellevel performance profiling and optimization
• Runtime selection, graph partitioning, and acceleration
• Systemlevel optimization across multiple simultaneous AI models
• Multitenant execution alongside domain workloads (control, vision, graphics, audio, safety)
• Agentic AI workloads and optimization
• Act as the technical escalation point for systemlevel issues involving latency, determinism, contention, isolation, and stability

AI Deployment Journey Ownership

• Define and standardize the AI deployment journey for customers:
1. Model evaluation (accuracy, latency, resource footprint)
2. Singlemodel optimization (CPU/GPU/accelerator efficiency)
3. Multimodel concurrency (pipelines running simultaneously)
4. Multitenancy and isolation across workloads and applications
5. Systemlevel tuning under real operating conditions
• Guide customers in transitioning from modelcentric thinking to systemcentric deployment
• Ensure AI workloads coexist predictably with:

• Robotics control loops and realtime pipelines
• Digital cockpit graphics, vision, and HMI stacks
• Safetycritical, deterministic, or longlifecycle software
• Building mission-critical AI reference architectures for easy and scalable deployment of AI across the large spectrum embedded and physical AI Customers.

MarketSpecific System Integration

• Oversee AI system deployments across multiple edge/physical AI domains, including:
• Robotics & Autonomy: perception, planning, sensor fusion, control, safety
• Digital Cockpit: visionAI, driver monitoring, incabin AI, graphics coexistence
• Industrial / Physical AI: inspection, monitoring, closedloop automation, autonomous agents
• Create key AI reference architectures as relevant to broad set of markets
• Ensure AI deployment strategies respect domainspecific constraints:
• Realtime guarantees and determinism
• Graphics + AI coexistence (especially in cockpit)
• Safety, isolation, and mixedcriticality requirements
• Power, thermal, and resource budgeting

Organizational Leadership

• Build, scale, and mentor a highperforming team with expertise in segments,
• Define roles across:
• AI inference and runtime optimization
• System software and scheduling
• Domainspecific AI deployment (robotics, cockpit, industrial)
• Establish consistent engagement models for:
• Early silicon and platform access
• AI deployment readiness assessments
• Prototypetoproduction transitions
• Ensure customer learning is captured, generalized, and reused
• Work internally with SDK and Core AI engineering teams to bring leading edge features into the customer front.

Platform, SDKs, and Roadmap Influence

• Serve as the key conduit from real deployments to internal roadmap and development strategy
• Translate customer AI deployment challenges into:
• SDK and runtime requirements
• Tooling, profiling, and observability improvements
• Platform and silicon architecture feedback
• Influence platform priorities to support:
• Multimodel concurrency
• Efficient scheduling and isolation
• Longlifecycle, mixedcriticality deployments
• Scalable AI deployment patterns across market segments

CrossFunctional Leadership

• Partner closely with:
• Platform architecture, SDKs, Core AI engineering and product management
• Silicon and system software engineering
• Ecosystem and strategic partnerships
• Align internal teams around a deploymentfirst view of AI success, not benchmarkdriven optimization only
• Define clear boundaries and handoffs between:
• Customer coengineering
• Core AI and SDK teams
• Partner and ecosystem enablement

PREFERRED EXPERIENCE:

• 17+ years of experience in AI systems performance and deployment in the markets of edge computing, robotics, embedded platforms, or physical AI
• Proven leadership experience managing senior technical teams
• Deep understanding of:
• AI inference runtimes and deployment tradeoffs
• CPU/GPU/NPU scheduling and contention
• Systemlevel performance, latency, and isolation
• Software frameworks and usage (multimedia, ROS2, OpenCV, gstreamer etc.)
• Industry leading inference frameworks (vLLM etc.)
• Strong background in:
• Embedded Linux and/or RTOS environments
• Multiprocess, multitenant system design
• Edge AI deployment at scale
• Runtimes and Offline tools
• Ability to engage credibly with customer's engineering leaders, AI architects and leaders
• Track record of transforming customer deployments into platform and roadmap feedback
• Hands-on leader who can get into technical details with the engineers as well as uplevel the complexity to the executives

Preferred / Differentiators

• Experience deploying AI in realtime or safetysensitive environments
• Background in robotics, autonomous systems, embedded/edge or digital cockpit platforms
• Experience with mixedcriticality systems (QNX, AUTOSAR Adaptive, realtime Linux)
• History of influencing multigeneration platform or silicon roadmaps
• Experience moving customers from PoC to volume production
• Experience with AMD NPU and GPU AI SW stacks and tools will be even better

PREFERRED LOCATION:

• San Jose / Santa Clara, CA or Austin, TX

This role is not eligible for visa sponsorship.

#LI-MH2

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.