AI Infrastructure Engineer

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.

• 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.

• 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 have:

• 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).

What does Mirantis offer you?

• Work with an established Silicon Valley leader in the cloud infrastructure industry;

- Work with exceptionally passionate, talented and engaging colleagues, helping Fortune 500 and Global 2000 customers implement next-generation cloud technologies;

- Be a part of cutting-edge, open-source innovation;

- Thrive in the high-energy environment of a young company where openness, collaboration, risk-taking, and continuous growth are valued;

- Professional development and training;

• Attend conferences and working groups;

- Company outings, happy hours, hackathons, and tech talks;

- Receive a competitive compensation package with a strong benefits plan.

It is understood that Mirantis, Inc. may use automated decision-making technology (ADMT) for specific employment-related decisions. Opting out of ADMT use is requested for decisions about evaluation and review connected with the specific employment decision for the position applied for. You also have the right to appeal any decisions made by ADMT by sending your request to [email protected]

By submitting your resume, you consent to the processing and storage of your personal data in accordance with applicable data protection laws, for the purposes of considering your application for current and future job opportunities.

We are a https://www.g2.com/reports/grid-report-for-container-management-spring-2022.embed?featured=mirantis-kubernetes-engine-formerly-docker-enterprise&secure%5Bgated_consumer%5D=7ed17484-74e3-4ce8-8ad6-b48b395fbf56&secure%5Btoken%5D=f4b909a5c1a2d1aa71dee93761486db5732a5b82abd47aa75f3353da41e3b92c&utm_campaign=gate-817340 Leader for Container Management in G2 (#2 after AWS)!

• 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).