Infrastructure Systems Engineer – Linux, Storage & Automation
Hands-on infrastructure engineer at Cerebras who deploys, automates, and maintains Linux-based compute and block/file/object storage systems using Python, Bash, and Ansible, while troubleshooting performance, networking, and virtualization issues across data center environments supporting AI supercomputing.
- Compensation
- Not disclosed
- Location
- Sunnyvale, United States
- Work setup
- Hybrid
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Software engineering
- Posted
Skills
Must have
- Strong hands-on experience administering and troubleshooting Linux systems
- Proficiency in Python and shell scripting, particularly Bash
- Practical experience with Ansible for automation and configuration management
- Experience with virtualization platforms such as KVM, VMware, or Proxmox
- Hands-on experience administering enterprise or distributed storage systems
- Working knowledge of block, file, and object storage; protocols like NFS, SMB, iSCSI, or S3
- Familiarity with Linux storage management: disk configuration, RAID, LVM, filesystems, mounts
- Ability to troubleshoot storage performance using IOPS, throughput, and latency metrics
- Strong debugging skills and methodical root cause analysis
- Working knowledge of TCP/IP, DNS, DHCP, routing, VLANs, and network troubleshooting
- Familiarity with Linux services, permissions, processes, package management, and system logs
- Experience using Git for version control and collaborative development
- Ability to own technical problems through resolution and communicate findings clearly
Nice to have
- Experience with storage platforms such as VAST Data, NetApp, Dell PowerScale, Pure Storage, or Ceph
- Familiarity with high-performance storage networking: RDMA, RoCE, or InfiniBand
- Experience with bare-metal provisioning: PXE boot, Kickstart, or cloud-init
- Familiarity with server management interfaces such as BMC, IPMI, or Redfish
- Experience with Docker, Kubernetes, or other container technologies
- Familiarity with infrastructure monitoring and centralized logging tools
- Experience supporting data center, AI/ML, or HPC environments
- Experience planning storage capacity, expanding storage systems, and supporting data migrations
Full description
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
The Role
We are looking for a hands-on engineer to deploy, automate, troubleshoot, and maintain Linux-based compute and data storage infrastructure. The ideal candidate combines strong Linux fundamentals with Python, Ansible, shell scripting, virtualization, and storage experience. They enjoy investigating complex problems, identifying root causes, and building automation that improves reliability and reduces manual work.
Responsibilities
- Deploy, configure, and maintain Linux servers across physical and virtual environments.
- Deploy and support data storage systems, including block, file, and object storage.
- Configure and troubleshoot storage connectivity, volumes, filesystems, permissions, and access from Linux hosts and virtual machines.
- Monitor storage capacity, performance, and availability; investigate latency, throughput, and connectivity issues.
- Develop Python and Bash scripts to automate provisioning, configuration, validation, and routine operational tasks.
- Build and maintain Ansible playbooks and roles for consistent, repeatable infrastructure deployments.
- Troubleshoot issues across operating systems, applications, networking, storage, and virtualization platforms.
- Investigate logs, analyze system behavior, and resolve performance, availability, and configuration problems.
- Manage virtual machines and troubleshoot hypervisor, virtual networking, and storage integration issues.
- Support server provisioning, operating system installation, patching, upgrades, and configuration management.
- Support data protection and recovery through snapshots, replication, backups, and restore validation.
- Implement monitoring, health checks, and alerts to identify problems early.
- Collaborate with engineering, networking, storage vendors, and data center operations teams to deploy and support infrastructure.