Technical Program Manager - Data Center Deployment Tools and Services

Overview

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.

We are seeking a Technical Program Manager to lead the execution of AMD Data Center Graphics hardware and software subsystem programs for CSP partners and enterprise customers. This role sits at the intersection of AI data center deployments, GPU platforms, virtualization, and customer enablement, owning programs from concept through execution.

You will play a critical role in driving successful AI Data Center and GPU cluster deployments, ensuring validation, optimization, and alignment with customer and business objectives. This position offers the opportunity to work closely with AMD s engineering, program, and customer teams to deliver industry-leading AI and compute solutions.

You are comfortable operating in complex, system-level environments involving hardware, software, networking, and AI workloads. You thrive in cross-functional settings, can translate technical detail into actionable program plans, and confidently engage with both engineering teams and external customers. You bring a structured, detail-oriented mindset while maintaining the flexibility required to manage fast-moving AI and data center programs. You are proactive, collaborative, and able to independently drive programs to completion.

• Lead and manage programs supporting AMD Instinct™ GPU products, including customer-facing AI, graphics, and compute deployments
• Own end-to-end AI Data Center and GPU cluster programs, from planning and validation through customer enablement and execution
• Provide strategic technical guidance to customers on server graphics, compute platforms, virtualization, and AI/ML workloads
• Oversee development and deployment of data center GPU containers and software stacks for customer testing and validation
• Collaborate with engineering teams to identify, track, and resolve technical issues across the product lifecycle
• Ensure new software functionality aligns with customer requirements and program objectives
• Define, plan, and drive program plans based on management and senior technical guidance
• Develop and manage program schedules, staffing plans, and dependencies across multi-disciplinary teams
• Maintain the Plan of Record (POR) and hold teams accountable for milestones and deliverables
• Track action items, manage risks, and proactively mitigate issues impacting schedule, cost, or quality
• Establish, enforce, and refine program management processes to improve operational efficiency
• Communicate status, risks, and escalations clearly to AMD leadership and stakeholders
• Represent programs in executive and engineering forums, providing concise and effective updates
• Build and maintain program management artifacts including PORs, statements of work, schedules, budgets, scope, and KPIs
• Incorporate customer feedback to guide internal teams and improve product and program outcomes

• Experience supporting data center GPU, graphics, and compute platforms in customer-facing environments
• Strong understanding of server architecture, including remote management, network topologies, and graphics software/hardware subsystems
• Proficiency with Linux installation, configuration, usage, and debugging
• Experience working with virtualized environments and virtual machine setup and management
• Familiarity with data center GPU software stacks such as AMD ROCm™ and/or NVIDIA CUDA
• Knowledge of distributed communication libraries and GPU-accelerated distributed memory…