Senior AI Infrastructure, Platform Operations Engineer

This is a fully remote position, open to applicants in Europe.

📋 Description

• Oversee the investigation and resolution of intricate infrastructure, networking, and platform-related incidents.

• Serve as a senior escalation point during critical events that impact service delivery.

• Provide support for expansive NVIDIA GPU infrastructure and high-performance networking settings.

• Diagnose issues related to Linux, Kubernetes, networking, storage, and hardware.

• Assess platform performance, capacity, stability, and reliability trends to pinpoint risks.

• Lead root cause analysis efforts and implement long-term corrective measures.

• Collaborate effectively with engineering teams, hardware vendors, and datacenter staff.

• Engage in major incident management and service restoration activities.

• Offer technical leadership for Kubernetes platform operations and supporting infrastructure services.

• Enhance platform reliability, observability, monitoring, and operational workflows.

• Automate repetitive operational tasks to boost efficiency.

• Contribute to operational readiness assessments, infrastructure modifications, upgrades, and new service implementations.

• Support AI-driven infrastructure services and operational capabilities via k0rdent AI.

• Assess and evaluate emerging technologies and operational methodologies.

• Mentor and guide AI Infrastructure & Platform Operations Engineers.

• Disseminate technical knowledge through documentation, training sessions, and operational reviews.

• Create and maintain operational standards, runbooks, troubleshooting manuals, and best practices.

• Assist in defining operational procedures, escalation pathways, and service reliability benchmarks.

• Act as a technical consultant during operational planning and initiatives for service enhancement.

⛳️ Requirements

• A minimum of 7 years of experience in infrastructure operations, platform operations, site reliability engineering, network operations, cloud operations, datacenter operations, or other relevant technical roles.

• Proficient in Linux administration and troubleshooting at an expert level.

• Strong knowledge of networking, including the ability to diagnose complicated performance, connectivity, and reliability issues.

• Extensive experience in managing Kubernetes within production environments.

• Background in supporting large-scale production infrastructure and distributed systems.

• Demonstrated experience in leading technical investigations and managing complex incidents.

• Experience in conducting root cause analysis and implementing long-term operational enhancements.

• Deep understanding of observability, monitoring, and service reliability principles.

• Exceptional troubleshooting and analytical skills across various infrastructure domains.

• Strong communication, collaboration, and stakeholder management abilities.

• Experience with NVIDIA GPU infrastructure and accelerated computing platforms, InfiniBand networking, NVIDIA UFM, AI infrastructure, HPC environments, Platform Engineering or SRE, large-scale Kubernetes operations, infrastructure automation, Infrastructure-as-Code, observability platforms like Grafana, Prometheus, ELK, or OpenTelemetry, performance analysis and optimization of distributed infrastructure platforms, as well as technical leadership, mentoring, or team lead experience is highly desirable.

🏝️ Benefits

• Operate within some of the most advanced AI infrastructure environments currently in production.

• Work with cutting-edge NVIDIA GPU technologies, Kubernetes platforms, and high-performance networking setups.

• Help establish operational standards and reliability practices for future AI infrastructure services.

• Influence the integration of AI-powered operational capabilities through k0rdent AI.

• Collaborate with highly skilled engineers to tackle complex infrastructure and platform challenges at scale.

• Join a growing organization that is heavily investing in AI infrastructure, platform services, and operational innovation.