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AI Infrastructure Engineer

vCluster LabsRemoteCustomer Engineering
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Salary
$140K - $165K USD
Job type
Full-time
Work mode
Remote
Posted
30 Mar 2026
Status
Open · checked 7d ago

About this role

An AI Infrastructure Engineer position is available remotely with vCluster to guide customers from bare metal GPU nodes to production-ready deployments. This role is ideal for an experienced infrastructure professional who enjoys driving technical pre-sale proofs of value and building reusable playbooks for GPU cloud builders.

Role Overview

As an AI Infrastructure Specialist at vCluster, you will work directly with neoclouds and AI Factories at the earliest and most critical stages of their technical journey. This is a hands-on technical role operating during the pre-sale phase as part of targeted proof of value engagements designed to reach production swiftly. You will help organizations offer Kubernetes as a managed service on bare metal GPU infrastructure by driving end-to-end deployments and collaborating closely with internal engineering teams.

Key Responsibilities

Lead end-to-end technical deployments for GPU neocloud and AI Factory customers, taking environments from initial bare metal setup to a validated vCluster platform.
Configure and troubleshoot bare metal GPU node infrastructure, encompassing CNI setup, GPU Operator configurations, distributed storage backends, and RDMA/InfiniBand.
Deploy and validate Kubernetes and vCluster to deliver robust, GPU-powered managed container environments.
Partner alongside customer technical teams to foster self-sufficiency so they can independently operate and scale their platforms.
Document reusable deployment architectures and playbooks that act as streamlined head starts for future customers and internal hires.
Serve as a vital feedback loop from the field into product and engineering roadmaps by surfacing recurring infrastructure hurdles.
Join sales teams during pre-sale discussions whenever deep infrastructure expertise is required to achieve a successful proof of value.

Requirements

5+ years of hands-on experience deploying and operating Kubernetes in production environments, ideally on bare metal or within high-complexity architectures.
Practical, hands-on knowledge of NVIDIA GPU Operators, CUDA tooling, and systems-level configuration specific to GPU nodes.
Deep understanding of CNI plugins, overlay networking, load balancing, and connectivity troubleshooting within layered setups.
Experience configuring persistent volumes, CSI drivers, and distributed storage systems such as Ceph, Rook, Weka, or Longhorn.
Strong operational agility with the ability to thrive in fast-moving, ambiguous environments where documentation and playbooks are written in real time.
A modern tech mindset that avoids legacy approaches in favor of versatile problem-solving across internal services and pipelines.

Nice to Have

Proficiency in writing automation scripts using Python, Bash, or Go.
Relevant professional certifications such as Certified Kubernetes Administrator (CKA) or practical experience writing custom Kubernetes Operators.
Familiarity with AI and machine learning concepts, including GPU scheduling, inference serving, and foundational LLM deployment tooling.
Experience building AI automation into documentation to enrich a shared team knowledge base.

Skills and Tools

Kubernetes
Python
LLM tooling and GPU scheduling
NVIDIA GPU Operators and CUDA
CNI plugins and networking
Distributed storage (Ceph, Rook, Weka, Longhorn)

Salary and Benefits

Competitive salary ranging from $140,000 to $165,000 USD per year, paired with equity options.
Premium insurance coverage including health, dental, vision, and life insurance plans for employees and eligible dependents.
Flexible working schedule centered around results rather than strict clock-in times.
Workplace flexibility that accommodates remote work environments and lifestyle changes.

About the Company

vCluster Labs is a venture-backed startup recognized as a leading platform for AI infrastructure, having raised over $28 million from top-tier investors like Khosla Ventures. Headquartered in San Francisco with a global remote-first team, the company builds open-source tenant isolation technology for Kubernetes, powering over 100,000 GPUs across numerous AI clouds and Fortune 500 enterprises. The organization prides itself on a culture driven by action, ownership, customer delight, open-source contribution, and defining tomorrow's technology standards.

How to Apply

Interested candidates should visit the official vCluster careers page to submit an application and join the remote team.

Skills and tech stack

PythonKubernetesLLM

Questions candidates ask

What is the salary range for the AI Infrastructure Engineer role?

The annual salary ranges from $140,000 to $165,000 USD, and the position also includes equity.

Is this position remote?

Yes, this is a remote-first position with a globally distributed team, though the company headquarters are located in San Francisco.

What level of experience is required?

Candidates must bring 5 or more years of experience deploying and operating Kubernetes in production environments, preferably on bare metal.

What are the primary technical focus areas for this job?

The role focuses heavily on bare metal GPU node configuration, NVIDIA GPU Operators, CNI and networking, distributed storage backends, and Kubernetes managed services.

What benefits are provided with this employment?

Benefits include a competitive salary with equity, premium health, dental, vision, and life insurance, a flexible working schedule, and workplace flexibility.

Ready to apply?

The application is on the official vCluster Labs careers page.

Apply on company site