Emerald AI
Member of Technical Staff - AI Cloud Infrastructure
Bay Area +2 · Hybrid · Staff · Full-time · Posted Aug 5, 2026
- Location
- Bay Area
Boston
Washington D.C. - Experience
- At least 7+ years; must include architecture and launch of a managed cloud or AI platform that reached production users.
About the job
Architect and build Emerald AI’s managed, power-flexible AI cloud infrastructure, including its platform, control plane, customer services, and operations.
What you'll do
- Design and launch managed GPU services, including tenant models, provisioning, service catalogs, and multi-provider capacity.
- Build control-plane services, customer interfaces, lifecycle automation, and usage metering integrated with billing.
- Operate and orchestrate multi-tenant GPU infrastructure, including Kubernetes and Slurm, parallel storage, partner onboarding, and service reliability.
What they ask for
- At least 7+ years of infrastructure or platform engineering experience, including architecting and launching a production managed cloud or AI platform.
- Strong experience with Kubernetes and Slurm offered as managed services.
- Production experience deploying or operating Lustre or a comparable parallel filesystem, such as GPFS, Weka, VAST, or BeeGFS.
- Cloud service fundamentals, deep Linux knowledge, infrastructure as code with tools such as Terraform and Ansible, programming in Python or Go, and familiarity with GPU infrastructure and high-performance networking.
Nice to have
- Experience at a GPU cloud, hyperscaler AI service, or HPC center delivering compute and storage as a service.
- Familiarity with NVIDIA reference architectures such as SuperPOD, GPUDirect Storage, NCCL debugging, and DCGM.
Tools
Kubernetes, Slurm, Lustre, GPFS, Weka, VAST, BeeGFS, Terraform
AI focus
Build and operate managed AI cloud infrastructure for GPU-based large-scale training and inference, with flexible power use to support sustainable AI growth.
Model-written summary · the original posting is authoritative