Senior AI Infrastructure and Platform Operations Engineer

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

📋 Description

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

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

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

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

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

• Direct root cause analysis efforts and implement long-term corrective actions.

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

• Engage in major incident management and service restoration operations.

• Offer technical leadership for Kubernetes platform operations and related 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 service launches.

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

• Assess emerging technologies and operational methodologies.

• Mentor and assist AI Infrastructure & Platform Operations Engineers.

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

• Develop and uphold operational standards, runbooks, troubleshooting manuals, and best practices.

• Help establish operational processes, escalation routes, and service reliability benchmarks.

• Provide guidance during operational planning and service enhancement initiatives.

⛳️ Requirements

• Over 7 years of experience in infrastructure operations, platform operations, site reliability engineering, network operations, cloud operations, datacenter operations, or comparable technical roles.

• Expert-level skills in Linux administration and troubleshooting.

• Proficient networking knowledge, including the diagnosis of complex performance, connectivity, and reliability challenges.

• Extensive experience operating Kubernetes in live production settings.

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

• Demonstrated experience leading technical investigations and managing intricate incidents.

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

• Strong grasp of observability, monitoring, and service reliability practices.

• Exceptional troubleshooting and analytical abilities across various infrastructure domains.

• Excellent communication, collaboration, and stakeholder management skills.

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

• Play a key role in defining operational standards and reliability practices for next-generation 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.

• Enjoy the flexibility of remote work.