Member of Technical Staff - AI Cloud Infrastructure

Architect managed services from 0→1, including GPU capacity productization, isolation boundaries, tenant models, provisioning flows, and service catalogs Build control-plane services, self-service customer interfaces, automated lifecycle systems, and usage metering integrated with billing Onboard and technically assess bare-metal GPU infrastructure partners Design and implement multi-tenancy across compute, storage, and networking with secure isolation, QoS, and encryption Manage Kubernetes and Slurm environments for large-scale training and inference Oversee node health, driver fleets, and kernel management across heterogeneous clouds Deploy and integrate parallel storage solutions such as Lustre, VAST, or Weka Define SLOs, observability standards, and incident response protocols Bridge internal operational standards with provider SLAs to deliver a reliable managed cloud product Requirements At least 7+ years of infrastructure or platform engineering experience Experience architecting and launching a managed cloud or AI platform that reached production users Strong experience with Kubernetes and Slurm as managed services Production experience deploying or operating Lustre or comparable parallel filesystems such as GPFS, Weka, VAST, or BeeGFS Understanding of parallel filesystem architecture, tuning, and failure modes Strong grasp of cloud service fundamentals, control planes, tenancy and isolation models, APIs, quota and metering systems, and operational service discipline Deep Linux systems knowledge Mature infrastructure-as-code practice with Terraform and Ansible Programming ability in Python or Go Familiarity with GPU infrastructure and high-performance networking using InfiniBand, RoCE, and RDMA Familiarity with the GPU software stack Preferred: experience at a GPU cloud, hyperscaler AI service, or HPC center delivering compute and storage as a service Preferred: familiarity with NVIDIA SuperPOD, GPUDirect Storage, NCCL debugging, and DCGM Preferred: experience with Lustre multitenancy features or service-provider VAST/Weka deployments Preferred: experience negotiating with and integrating multiple infrastructure vendors Preferred: experience running object storage at scale with S3, Ceph, or MinIO, including data tiering Preferred: experience building billing, metering, or FinOps pipelines Must be located in or willing to locate to an Emerald AI hub Must address ability to work in the United States Core Competencies Demonstrates expertise in architecting and launching managed cloud platforms, with a strong focus on Kubernetes, Slurm, and parallel filesystem solutions. Proficient in infrastructure-as-code practices and capable of integrating GPU infrastructure for high-performance computing environments. Highest-signal resume keywords Kubernetes Management Slurm Administration Parallel Filesystem Deployment Infrastructure-as-Code with Terraform Python or Go Programming ATS Optimization Keywords Hard Skills Infrastructure Engineering Cloud Service Fundamentals Multi-Tenancy Design Linux Systems Knowledge GPU Infrastructure Familiarity Control Plane Architecture APIs and Metering Systems Operational Service Discipline Incident Response Protocols Usage Metering Industry Keywords Managed Cloud AI Platform High-Performance Computing GPU Cloud Hyperscaler AI Service Tools & Technologies Terraform Ansible Lustre VAST Weka InfiniBand RoCE RDMA S3 Ceph #J-18808-Ljbffr Jobtailor