AI Datacenter System Management Architect

AMD; Santa Clara (CA); Sur place; USD 180 000 - 240 000; Plein temps

Résumé du poste

AMD in Santa Clara, CA is seeking an AI Instinct System Management Architect to define the architecture for system management across AI datacenter platforms. You will own reference designs and blueprints for deploying, integrating, and operating system management at rack and pod scale.

This role blends deep technical leadership with customer engagement, shaping security, observability, and manageability features that enable scalable AI workloads and reliable datacenter infrastructure.

Qualifications

• Expert background in systems or platform software architecture for system management.
• Deep expertise in BMC firmware stacks, telemetry, inventory, alerting, and management protocols.
• Strong knowledge of DMTF standards (MCTP, PLDM, SPDM, Redfish), platform security, and management networking.
• Experience with PCIe, CXL, NVMe interconnects and cluster schedulers (Kubernetes, Slurm).
• Proven ability to combine technical leadership with customer engagement for scalable AI datacenter deployments.

Responsabilités

• Define and drive architecture for system management across AI datacenter platforms.
• Develop reference designs and blueprints for deploying OS management at scale.
• Ensure compatibility with industry standards (Redfish, DMTF) and customer monitoring stacks.
• Collaborate with customers to align with DCIM/ITSM environments and lead proofs of concepts.
• Produce architectural collateral and telemetry baselines for customer readiness.

Connaissances

Systems architecture

BMC firmware

DMTF standards

PCIe/CXL/NVMe

Kubernetes/ Slurm

C/C++

Python/Go

Outils

Prometheus

Loki

ELK

OpenTelemetry

Description du poste

AMD in Santa Clara, CA is seeking an AI Instinct System Management Architect to define the architecture for system management across AI datacenter platforms. You will own reference designs and blueprints for deploying, integrating, and operating system management at rack and pod scale.

This role blends deep technical leadership with customer engagement, shaping security, observability, and manageability features that enable scalable AI workloads and reliable datacenter infrastructure.