Sr. Manager Ai Systems Validation ArchitectAt 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.AMD is seeking a Sr. Manager AI Systems Validation Architect to provide company-level technical leadership in defining how AMD validates AI platforms as production-ready, deployable data center solutions at hyperscale.This highly technical and people leadership role is responsible for validation architecture across:Server-level systemsRack-level deployment environmentsCluster-scale AI infrastructures operating in real-world data centersYou will define validation approaches not just in lab environments, but in conditions that mirror hyperscale deployment realities—including:Large-scale rack bring-upCluster provisioning and fleet validationData center integration and operations readinessThis role shapes validation strategy at the architectural level, ensuring alignment across CPU, GPU, networking, system architecture, firmware, and distributed software domains.You will lead a small team of senior architects, while personally operating as a hands-on technical authority—driving system-level validation, influencing cross-functional teams, and guiding AMD AI platforms from design validation to production deployment readiness in data centers at scale.Management and mentoring of a small team of highly technical validation engineers and architectsValidation Architecture (Lab ? Data Center Reality)Architect validation strategies for:Server-level AI platforms (CPU, GPU, memory, IO, firmware, system software)Rack-level systems (power delivery, thermals, networking fabric, failure domains, multi-node integration)Cluster-scale deployments (distributed systems behavior, orchestration, scheduling, resiliency, failover)Define validation strategies that reflect hyperscale deployment environments, including:Rack bring-up, provisioning, and fleet rolloutCluster qualification under real-world workloadsData center networking integration (fabric, storage, control planes)Failure injection, fault isolation, and recovery validationData Center Deployment & Operational ValidationDrive validation methodologies for full-stack deployment readiness, including:Hardware ?
firmware ? OS ? orchestration stack bring-upCluster provisioning and configuration management workflowsIntegration with orchestration platforms (Kubernetes, Slurm, internal schedulers)Partner with platform, SRE, and infrastructure teams to validate:Cluster reliability, availability, and serviceability (RAS)Scale-out behavior under load and failure conditionsReal-world operational scenarios (node failure, rack isolation, network partition, degraded performance)Debug Leadership (System + Fleet + Production)Lead and guide complex debug across:Silicon interactions (CPU/GPU)Firmware and system softwareNetworking and distributed systemsData center deployment environments and clustersSupport drive root cause analysis for issues seen in:Lab environmentsPre-production clustersData center deployments / fleet-scale validation environmentsHelp provide requirements and even participate on development of frameworks for:Fleet-level telemetry correlationFailure reproduction at scaleCross-layer debug (HW + SW + distributed system behavior)SRE / Reliability Engineering InfluenceDefine validation approaches aligned with SRE principles, including:Observability, metrics, and telemetry-driven validationChaos/failure testing and resiliency validationSLA/SLO-driven validation criteriaPartner with SRE and infrastructure teams to ensure:Systems are production-hardened before deploymentValidation includes operational readiness, not just functional correctnessLeadership & Cross-Org InfluenceLead and manage a small team of senior architectsDrive technical direction across silicon, platform, and software orgsAct as a system-level authority bridging validation, infrastructure, and deployment teamsRepresent validation architecture in executive and cross-functional forumsThe successful candidate is a recognized system-level leader with deep experience in data center systems, cluster-scale environments, and large-scale platform validation.You are equally comfortable:Managing a small team of highly technical validation engineers/architectsDriving architecture for validation at the rack and cluster levelDebugging complex multi-node failures in real environmentsWorking cross-functionally with hardware, software, and infrastructure teamsOperating in hyperscale data centers (Meta, Google, AWS, etc.)You bring:A strong systems mindsetExperience with real-world deployments (not just lab validation)The ability to scale impact through both leadership and technical depthPreferred experienceExtensive experience in data center platforms, hyperscale infrastructure, or large distributed systems environmentsManaging and mentoring small engineering teamsDirect experience with rack bring-up and cluster deployment workflowsFleet-scale validation or infrastructure qualificationData center operations or infrastructure engineeringStrong background in distributed systems, cluster orchestration, and schedulingNetworking (Ethernet, InfiniBand, RDMA, fabrics)Observability systems (metrics/logging/tracing)Experience in roles such as SRE, infrastructure engineering, production engineering, or data center validationSystem-level or fleet-level debugging in production-like environmentsProven experience debugging issues across hardware (CPU/GPU/platform), firmware / BIOS / BMC, OS / drivers / distributed software stacks, cluster or data center environmentsExperience with failure injection, chaos testing, or reliability validationLarge-scale workload validation (AI/ML training, HPC, distributed compute)Hands-on skills in scripting, automation, and test toolingData-driven debugging and telemetry analysisExperience influencing large organizations without direct authorityStrong ability to communicate across engineering teams, infrastructure/ops teams, executive leadershipAcademic credentialsBachelor's degree in electrical engineering, Computer Engineering, Computer ScienceAdvanced degree or equivalent industry experience preferred