Moonlite delivers high-performance AI infrastructure for organizations running intensive computational research, large-scale model training, and demanding data processing workloads.We provide infrastructure deployed in our facilities or co-located in yours, delivering flexible on-demand or reserved compute that feels like an extension of your existing data center. Our team of AI infrastructure specialists combines bare-metal performance with cloud-native operational simplicity, enabling research teams and enterprises to deploy demanding AI workloads with enterprise-grade reliability and compliance.

Your Role:

We are seeking a Senior Infrastructure Engineer to design, deploy, and manage the physical infrastructure powering Moonlite's GPU clusters and high-performance computing environments. You will be responsible for building and operating scalable, reliable compute, storage, and networking infrastructure that powers AI training / inference and research workloads. This role focuses on the hardware and provisioning layer—servers, GPUs, networking equipment, firmware, and bare-metal provisioning systems—ensuring our infrastructure is tuned for performance and reliability. You will partner closely with network engineers, systems engineers, and SREs to deliver robust infrastructure at scale.

Job Responsibilities

Infrastructure Design & Deployment: Architect and implement GPU and compute infrastructure at the server, rack, and system level for AI workloads across co-located data center environments.
Bare-Metal Provisioning: Deploy and manage bare-metal servers using provisioning tools like Canonical MAAS, building automated workflows for severe lifecycle management from installation through decommissioning.
Hardware & Firmware Management: Develop and maintain systems to monitor hardware health, manage firmware updates across compute/storage/network equipment, and automate recovery processes.
GPU Operations: Trouble GPU-related performance issues at the driver, kernel, or firmware level and optimize configurations for training and inference workloads.
Infrastructure Automation: Build automation using Ansible, Terraform, and Python to eliminate manual provisioning, streamline patching processes, and enable scalable infrastructure operations.
Performance Monitoring: Monitor system performance, identify bottlenecks in compute/storage/networking layers, and proactively address reliability issues or capacity issues.
Cross-Team Collaboration: Work closely with network engineers, systems engineers, and SREs to ensure cohesive infrastructure operations and seamless integration with Kubernetes and platform orchestration layers.
Vendor Management: Serve as primary point of contact for hardware escalations, RMAs (Return Material Authorization), and vendor relationship for compute/storage/networking equipment.

Requirements

Experience: 5+ years in infrastructure engineering, systems engineering, or hardware-focused roles, preferably with AI/HPC workloads.
Linux Expertise: Strong background in Linux systems administration, performance tuning, and troubleshooting at the system level.
Bare-Metal Provisioning: Hands-on experience with bare-metal provisioning tools (MAAS or similar) and automated deployment workflows.
DCIM & Documentation: Familiarity with data center infrastructure management tools (NetBox, Device42, or similar) for asset tracking, network documentation, and maintaining infrastructure source of truth.
Hardware & GPU Systems: Familiarity with server hardware, GPU configurations, drivers, and system level performance optimization.
Automation Skills: Proficiency with Ansible, Terraform, and scripting (Python, Bash) for infrastructure automation and operational efficiency.
Infrastructure Operations: Experience deploying and maintaining physical infrastructure in production data center environments.
Problem-Solving: Ability to troubleshoot complex hardware, firmware, and system issues under pressure.
Collaboration: Comfortable working with cross-functional teams including network engineers, systems engineers, and platform developers to resolve infrastructure challenges.

Preferred Qualifications

Experience with GPU workload orchestration platforms (Kubernetes, SLURM) and their infrastructure requirements.
Familiarity with high-performance networking (InfiniBand, RDMA, RoCE) and spine-leaf network architectures.
Experience with monitoring and observability tools (Prometheus, Grafana).
Understanding of Kubernetes infrastructure requirements (compute, storage, networking layer)
Exposure to co-located data center operations or building infrastructure for regulated environments
Background supporting research institutions, HPC facilities, or enterprise AI infrastructure

Key Technologies

Linux, Canonical MAAS, NetBox, Terraform, Ansible, Python, NVIDIA GPU Drivers/Tools, High-Performance Networking, Enterprise Storage Systems, Prometheus, Grafana

Why Moonlite

Build the Future of AI Infrastructure: Join a pioneering team shaping scalable solutions for the enterprise. Your work will directly impact the deployment and usability of AI at scale.
Hands-On Ownership: As an early engineer, you'll have end-to-end ownership of projects and the autonomy to influence our product and technology direction.
Collaborate with Experts: Work alongside seasoned engineers and industry professionals passionate about high-performance computing, innovation, and problem-solving.
Start-Up Agility with Industry Impact: Enjoy the dynamic, fast-paced environment of a startup while making an immediate impact in an evolving and critical technology space.

We offer a competitive total compensation package combining a competitive base salary, startup equity, and industry-leading benefits. The total compensation range for this role is $165,000 – $225,000, which includes both base salary and equity. Actual compensation will be determined based on experience, skills, and market alignment. We provide generous benefits, including a 6% 401(k) match, fully covered health insurance premiums, and other comprehensive offerings to support your well-being and success as we grow together.

Moonlite AI

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