Technical Product Manager – Infrastructure and Kubernetes Platform Networking - Advanced Micro Devices, Inc

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Technical Product Manager – Data Center GPU

THE TEAM:

AMD's Data Center GPU organization is transforming the industry with our AI based Graphic Processors. Our primary objective is to design exceptional products that drive the evolution of computing experiences, serving as the cornerstone for enterprise Data Centers, (AI) Artificial Intelligence, HPC and Embedded systems. If this resonates with you, come and joining our Data Center GPU organization where we are building amazing AI powered products with amazing people.

THE ROLE:

We're seeking an experienced Technical Product Manager to drive our networking infrastructure products for GPU-accelerated Kubernetes environments, with particular focus on high-performance RDMA fabric management and orchestration. This role sits at the intersection of high-performance computing, cloud-native architectures, and large-scale AI infrastructure networking.

The impact you will have:

• Design and deliver next-generation fabric management solutions for AI infrastructure
• Drive architectural decisions that enable customers to scale their AI training and inference workloads
• Build products that power some of the world's largest AI computing clusters
• Define the future of network fabric management for large-scale AI environments

THE PERSON:

The ideal candidate will combine technical expertise with business acumen to drive product development from conception to market success. Excellence in stakeholder management and cross-functional leadership and strong analytical and quantitative skills with data-driven decision-making skills.  The candidate will have outstanding written and verbal communication abilities and partner across the organization internally and with customers.

KEY RESPONSIBILITIES:

• Own and evolve the product roadmap for networking solutions specific to GPU-enabled Kubernetes clusters, with emphasis on RDMA fabric management and orchestration
• Lead the design and delivery of an AI Network Fabric Manager, including topology-aware scheduling, congestion management, and QoS policies
• Drive architectural decisions for fabric management across multi-rack, multi-cluster environments
• Partner with engineering teams to architect and deliver networking solutions that maximize GPU utilization and minimize fabric congestion
• Define and track key performance metrics for network throughput, latency, and reliability in GPU-accelerated environments
• Work closely with customers running large-scale AI training clusters to understand their networking requirements and pain points
• Manage relationships with hardware vendors and cloud providers to ensure optimal network performance for GPU workloads

REQUIRED QUALIFICATIONS:

• Several years of product management experience, with a focus on infrastructure or networking products
• Deep expertise in RDMA networking architectures, including RoCE, IB fabric management, and subnet management
• Strong background in network fabric design for large-scale AI clusters (1000+ nodes)
• Experience designing and implementing fabric managers for HPC or AI workloads
• Hands-on experience with GPU-accelerated Kubernetes clusters and associated networking challenges
• Previous experience at a major cloud service provider (CSP) managing large-scale infrastructure products
• Understanding of congestion control mechanisms and QoS in RDMA environments

PREFERRED QUALIFICATIONS:

• Experience designing topology-aware scheduling systems for AI workloads
• Deep understanding of network telemetry and fabric monitoring systems
• Background in performance optimization for multi-GPU and multi-node training environments
• Experience with container networking security and isolation in GPU environments
• Expertise in fabric management APIs and control plane design
• Understanding of network congestion management in AI training environments
• Knowledge of GPU device plugin architecture and networking implications
• Experience with fabric-level performance debugging and optimization

LOCATION: 

• Santa Clara, California preferred but open to other locations

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At AMD, your base pay is one part of your total rewards package.  Your base pay will depend on where your skills, qualifications, experience, and location fit into the hiring range for the position. You may be eligible for incentives based upon your role such as either an annual bonus or sales incentive. Many AMD employees have the opportunity to own shares of AMD stock, as well as a discount when purchasing AMD stock if voluntarily participating in AMD’s Employee Stock Purchase Plan. You’ll also be eligible for competitive benefits described in more detail here.

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.