AI Infrastructure Engineer

Mirantis

7d•Remote

About The Position

We are looking for an AI Infrastructure Engineer to join our global team responsible for managing and supporting large-scale AI infrastructure environments. You will help ensure the availability, performance, and operational stability of critical AI infrastructure platforms, working closely with a distributed team across regions to provide continuous coverage and support. This is an opportunity to work hands-on with some of the most advanced Kubernetes-based AI infrastructure in production today, while contributing to the platforms and processes that keep it running reliably at scale.

Requirements

Proven experience managing and operating large-scale production systems (bare-metal and/or cloud).
Solid working knowledge of Kubernetes with excellent, demonstrable troubleshooting skills.
Experience configuring, customizing, and extending logging and monitoring tools (e.g., Prometheus, Grafana, ELK, or similar).
Experience with infrastructure automation technologies and Infrastructure-as-Code practices (e.g., Ansible, Terraform, or similar).
Effective verbal and written communication skills in English.
Strong analytical and problem-solving skills, with the ability to work through complex, ambiguous technical issues.
Willingness to occasionally work weekends and holidays.

Nice To Haves

Previous experience building, scaling, and running High-Performance Computing (HPC) environments.
Hands-on experiences with managing large scale Kubernetes platforms in production.
A good understanding of NVIDIA GPU technologies and the associated software stack.
Proficiency in scripting languages (e.g., Python, Bash, Go).

Responsibilities

Manage and operate production AI infrastructure environments.
Lead incident response and troubleshooting efforts and deliver timely service restoration during outages or performance degradations .
Troubleshoot infrastructure and networking issues across bare-metal and/or cloud environments with multiple vendors.
Conduct root cause analysis and drive product and operational improvements.
Contribute and improve operational documentation and knowledge base.
Collaborate with global team members across time zones to ensure continuous operational coverage, including occasional work during weekends and holidays.