Remote configuration is available for this AI Infrastructure Engineer position at vCluster Labs, a role focused on guiding GPU cloud providers and AI factories from bare metal setup to production-ready deployments. This position suits an experienced infrastructure professional who enjoys direct customer collaboration, pre-sales technical proof of value, and shaping foundational deployment playbooks.
Role Overview
As an AI Infrastructure Specialist at vCluster Labs, the professional works directly with clients at the earliest stage of their journey, moving from bare metal GPU nodes to production deployments. Operating primarily pre-sale within proof of value engagements, the engineer builds reusable playbooks and acts as a vital feedback loop between field challenges and the internal product team.
Key Responsibilities
Direct end-to-end technical deployments for GPU neocloud and AI Factory customers, ranging from initial bare metal setup to a validated vCluster environment.
Configure and troubleshoot bare metal GPU node infrastructure, covering CNI setup, GPU Operators, distributed storage, and RDMA/InfiniBand.
Deploy and validate Kubernetes and vCluster instances to deliver GPU-backed managed Kubernetes services.
Collaborate alongside customer teams to foster independence in operating and scaling the platform.
Produce documentation and reusable deployment architectures to accelerate future customer onboarding.
Partner with the Engineering and Product departments to channel field feedback into roadmap improvements.
Assist the Sales division during pre-sales technical evaluations and proof of value demonstrations.
Requirements
Five or more years of hands-on experience deploying and managing Kubernetes within production settings, particularly on bare metal or highly complex architectures.
Practical familiarity with NVIDIA GPU Operators, CUDA tooling, and systems-level node configurations.
Extensive background in networking concepts such as CNI plugins, overlay networks, load balancing, and connectivity diagnostics.
Proven expertise in persistent storage configuration, CSI drivers, and distributed storage systems like Ceph, Rook, Weka, or Longhorn.
Ability to thrive in fast-paced, ambiguous environments while establishing processes dynamically.
Alignment with a modern technology stack that avoids legacy systems in favor of comprehensive infrastructure problem-solving.
Nice to Have
Practical automation capabilities utilizing Python, Bash, or Go.
Professional certifications like CKA or experience authoring Kubernetes Operators.
Familiarity with AI and machine learning ecosystems, including inference serving, GPU scheduling, and large language model deployment tools.
Background in building automated documentation systems for shared knowledge management.
Skills and Tools
Kubernetes
vCluster
NVIDIA GPU Operators
CUDA
CNI
RDMA
InfiniBand
Ceph
Rook
Weka
Longhorn
Python
Bash
Go
CKA
Slurm
Ray
Salary and Benefits
Annual salary ranging from €90K to €105K alongside equity and bonus offerings.
Comprehensive insurance packages covering health, dental, vision, and life (varied by country).
Flexible daily working schedules tailored around personal results rather than rigid hours.
Workplace location flexibility to accommodate changing life circumstances.
About the Company
vCluster Labs is a venture-backed startup that has secured over $28M from investors including Khosla Ventures.
The organization is headquartered in San Francisco within the Salesforce Tower and operates with a distributed, remote-first team.
It is the creator of vCluster, an open-source tenant isolation platform with over 11,000 GitHub stars and millions of tenant clusters created.
The enterprise powers more than 100,000 GPUs and 1 million CPUs across numerous AI clouds and Fortune 500 organizations.
How to Apply
Candidates should visit the official vCluster Labs careers page to submit an application for this opportunity.
