System Solutions Architect -Large Clusters for AI & HPC workloads

System Solutions Architect - Large Clusters for AI & HPC workloads

2 days ago Be among the first 25 applicants

This range is provided by AMD. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

About AMD

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.

The Role

The AMD Datacenter GPU team is seeking an experienced System Solutions Architect to join our team focused on enabling large clusters for AI inference and training workloads.

The Person

The ideal candidate will be a technical expert in Kubernetes-based AI infrastructure with deep knowledge of datacenter-level solutions for AI inference and training. This role offers the opportunity to work at the cutting edge of AI infrastructure, solving complex technical challenges and helping customers implement transformative AI solutions at-scale.

Key Responsibilities

Lead customer technical discovery with data / ML, platform, and infrastructure stakeholders; map business goals to AI workloads (training, fine-tuning, inference) and success metrics.

Assess current state (Kubernetes, GPUs / accelerators, storage, fabric, security, MLOps) and identify gaps, risks, and required POCs.

Shape reference architectures for large AI clusters (rack design, GPU topology, RoCE / InfiniBand, NVMe / parallel FS, multi-tenant K8s) aligned to customer constraints (power, cooling, space).

Translate model requirements into capacity and performance plans (tokens / sec, latency, throughput) and create BoMs with scaling paths.

Partner with the business development and product teams to build ROI / TCO models (CapEx / OpEx, $ / token, $ / inference) and craft the value story.

Support draft of technical sections of RFIs / RFPs; produce architecture diagrams, deployment plans, and implementation timelines.

Partner with program & engineering teams to define POC success criteria, test plans, and exit reports.

Collaborate with product management to foster product roadmap improvements.

Preferred Experience

Kubernetes-based AI infrastructure design and implementation

Load balancing strategies for high-volume inference workloads

Specialized operators for AI inference at scale

SLURM-based HPC cluster management for AI workloads

Network design for high-throughput GPU clusters

Storage architectures optimized for AI data pipelines

Infrastructure automation and orchestration tools

Performance optimization for large-scale inference deployments

Knowledge of infrastructure-as-code tools (Terraform, Ansible, etc.)

Familiarity with cloud-native observability and monitoring solutions

Understanding of security considerations for AI infrastructure

Solid years of experience designing and implementing large-scale infrastructure solutions

Deep knowledge of Kubernetes and container orchestration technologies

Hands‑on experience with AI / ML workloads in production environments

Strong understanding of datacenter networking and storage architectures

Experience with GPU‑accelerated computing environments

Proven track record of creating technical documentation and reference architectures

Excellent communication skills with the ability to explain complex technical concepts

Experience working directly with customer technical teams

Academic Credentials

Bachelor’s degree or higher in Computer Science, Electrical Engineering or closely related field.

LOCATION

San Jose, CA

Benefits

Benefits offered are described : AMD benefits at a glance.

EEO Statement

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.

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