Member of Technical Staff – AI Cloud Infrastructure

Emerald AI

Senior infrastructure engineer architecting Emerald AI’s flexible managed cloud for AI data centers. Building Kubernetes, Slurm, multi-tenant GPU, storage, and billing platforms.

Posted 8/6/2026full-timeSan Francisco • California, District of Columbia, Massachusetts • 🇺🇸 United StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

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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 ManagementSlurm AdministrationParallel Filesystem DeploymentInfrastructure-as-Code with TerraformPython or Go Programming

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Infrastructure EngineeringCloud Service FundamentalsMulti-Tenancy DesignLinux Systems KnowledgeGPU Infrastructure FamiliarityControl Plane ArchitectureAPIs and Metering SystemsOperational Service DisciplineIncident Response ProtocolsUsage Metering

Tools & Technologies

TerraformAnsibleLustreVASTWekaInfiniBandRoCERDMAS3Ceph

Industry Keywords

Managed CloudAI PlatformHigh-Performance ComputingGPU CloudHyperscaler AI Service

Tech Stack

Tools & technologies

AnsibleCloudGoKubernetesLinuxNode.jsPythonTerraform

About the role

Key responsibilities & impact

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

What you’ll need

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

Benefits

Comp & perks

Competitive pay + equity
Stock options
Medical benefits
Dental benefits
Vision benefits
401(k) matching
Flexible location
2 WFH days/week
Collaborative, low-ego environment
Opportunity to influence strategy, GTM, org design, and customer/investor engagement from day one
Reasonable accommodations for applicants with disabilities