Sr. Reliability Engineer at Super Micro Computer

Merindad de Sotoscueva, Castile and León, Spain -

Full Time

Start Date

Immediate

Expiry Date

03 Jan, 26

Salary

165000.0

Posted On

05 Oct, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Linux, Containers, Kubernetes, GPU Compute Clusters, Observability Tools, Scripting, Security, Network Protocols, Collaboration, Communication

Industry

Computer Hardware Manufacturing

Description

Job Req ID: 26861 About Supermicro: Supermicro® is a Top Tier provider of advanced server, storage, and networking solutions for Data Center, Cloud Computing, Enterprise IT, Hadoop/ Big Data, Hyperscale, HPC and IoT/Embedded customers worldwide. We are the #5 fastest growing company among the Silicon Valley Top 50 technology firms. Our unprecedented global expansion has provided us with the opportunity to offer a large number of new positions to the technology community. We seek talented, passionate, and committed engineers, technologists, and business leaders to join us. Job Summary: As a Cloud Reliability Engineer for our Linux-based AI cloud platforms, you will help us deploy, scale, and ensure high availability, performance, scalability, and security across GPU-accelerated compute clusters, Kubernetes workloads, and supporting storage/network infrastructure. You’ll bridge Dev and Ops by automating infrastructure deployment, enhancing observability, and applying SRE best practices to support reliable AI and MLOps environments.Essential Duties and Responsibilities: Includes the following essential duties and responsibilities (other duties may also be assigned): Cloud Infra Automation: Design and provision cloud infrastructure using Infrastructure as Code (Terraform, Ansible, or Helm) on bare metal or cloud platforms. Develop custom automation and tooling in Python or Go to extend deployment workflows and streamline operations. Platform Reliability: Deploy, scale, maintain, and optimize uptime for AI cloud services including GPU clusters, Kubernetes (K8s), and storage systems (e.g., Ceph, BeeGFS, or Weka). Understand the tools required to benchmark and assure consistent application performance. Monitoring & Alerting: Implement observability tools (e.g., Prometheus, Grafana, ELK, Loki, Fluentd) to monitor system health and alert on anomalies or performance degradation. Capacity Planning: Analyze usage trends and forecast infrastructure needs to support AI workloads and large-scale model training/inference. Incident Management: Lead root cause analysis and resolution for system outages or degraded performance. Define and maintain service level objectives (SLOs), indicators (SLIs), and agreements (SLAs) aligned with uptime and performance goals. CI/CD Integration: Collaborate with DevOps and MLOps teams to ensure reliable delivery pipelines using GitLab CI/CD, ArgoCD, or similar tools. Security & Compliance: Harden Linux systems, manage TLS certificates, and enforce secure access controls via Role-Based Access Control (RBAC), LDAP-integrated SSO, TLS, and network segmentation policies. Documentation & Playbooks: Maintain clear, version-controlled documentation, including architecture diagrams, runbooks, and incident response playbooks to support cross-team knowledge transfer and rapid onboarding. Qualifications: Bachelor’s degree in Computer Science, Engineering, or a related field—or equivalent experience and 8 years of experience in the areas below Proficiency in Linux (Ubuntu, RHEL/CentOS), containers (Docker, Podman), and orchestration (Kubernetes). Experience managing GPU compute clusters (NVIDIA / CUDA, AMD / ROCm) Hands-on experience with observability tools (Prometheus, Grafana, Loki, ELK, etc.). Strong scripting and coding skills (Bash, Python, or Go). Exposure to secure multi-tenant environments and zero trust architectures. Familiarity with network protocols, DNS, DHCP, BGP, ROCEv2, and InfiniBand or high-throughput Ethernet fabrics. Excellent collaboration and communication skills for cross-team, partner, and customer initiatives Preferred Qualifications: Understanding of AI/ML reference architectures and experience with workflows, MLFlow, or Kubeflow. Familiarity with storage backends optimized for AI (CephFS, BeeGFS, WekaFS). Prior experience in bare-metal provisioning via PXE, Ironic, or Foreman. Understanding of NVIDIA GPU telemetry and NCCL testing for performance benchmarking. Familiarity with ITIL processes or structured change management in production systems is a plus. Certifications: CKA, CKAD, Linux+, or related credentials. Salary Range $145,000 - $165,000 The salary offered will depend on several factors, including your location, level, education, training, specific skills, years of experience, and comparison to other employees already in this role. In addition to a comprehensive benefits package, candidates may be eligible for other forms of compensation, such as participation in bonus and equity award programs.EEO Statement Supermicro is an Equal Opportunity Employer and embraces diversity in our employee population. It is the policy of Supermicro to provide equal opportunity to all qualified applicants and employees without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veteran status or special disabled veteran, marital status, pregnancy, genetic information, or any other legally protected status.

Responsibilities

As a Cloud Reliability Engineer, you will deploy, scale, and ensure high availability across GPU-accelerated compute clusters and Kubernetes workloads. You will also automate infrastructure deployment and enhance observability to support reliable AI and MLOps environments.