AI Infrastructure System Engineer

About the Role

At the company, you’ll build and operate one of the world’s largest GPU fleets used for frontier model training and inference. This isn’t a traditional infrastructure role—we’re looking for engineers who love building systems, automating everything, and solving problems at massive scale.

If you enjoy writing software more than clicking dashboards, obsess over eliminating manual work, and want to build infrastructure that manages tens of thousands of GPUs autonomously, we’d love to talk.

Responsibilities

• Design and build fleet automation systems that provision, validate, deploy, upgrade, repair, and retire GPU clusters with minimal human intervention.

• Build AI Infrastructure Agents that automate deployment, root-cause failures, incident triage, and autonomous remediation.

• Develop Fleet Intelligence platforms that continuously monitor hardware health, firmware, networking, storage, thermals, and workload performance to predict failures before they impact customers.

• Build software that maximizes GPU availability, utilization, performance, and reliability across thousands of accelerators.

• Create automated validation systems for GPUs, InfiniBand/RoCE fabrics, NVLink/NVSwitch, storage, and distributed AI workloads.

• Build internal platforms and developer tools that allow infrastructure to be managed through software—not manual operations.

• Continuously improve deployment velocity, reliability, and operational efficiency through automation.

• Partner closely with hardware, networking, platform, and AI teams to push the limits of AI infrastructure.

Requirements

• 3+ years building distributed systems, infrastructure platforms, or large-scale backend software.

• Strong software engineering skills in Python, Go, or Rust .

• Experience building platforms, automation systems, or developer infrastructure.

• Experience with Linux, Kubernetes, Terraform, Ansible, or similar infrastructure technologies.

• Strong systems thinking with the ability to understand problems across hardware and software.

• A passion for solving complex infrastructure challenges through software.

• An automation-first mindset —if a task is repeated, your instinct is to build a system to eliminate it.

Bonus Experience

• GPU infrastructure, CUDA, NCCL, NVLink/NVSwitch

• InfiniBand or RoCE networking

• Bare-metal provisioning and lifecycle management

• Large-scale AI training or inference clusters

• Hardware health monitoring and predictive failure detection

• Distributed storage systems

• AI agents and autonomous infrastructure operations

About the company

The company, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month.

Application Policy

Please read each role carefully and apply to the position best suited to you. Candidates are limited to 6 applications within a 90-day period, and applications beyond that limit will be automatically rejected. You may apply to additional roles 90 days after your last application.

Equal Opportunity

The company is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

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