Infrastructure Systems Engineer – Linux, Storage & Automation

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.

Document configurations, troubleshooting procedures, and operational runbooks.

Qualifications

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 concepts, with practical experience in protocols such as NFS, SMB, iSCSI, or S3.

Familiarity with Linux storage management, including disk configuration, RAID, LVM, filesystems, and mount management.

Ability to troubleshoot storage performance using metrics such as IOPS, throughput, and latency.

Strong debugging skills and a methodical approach to 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.

Preferred Qualifications

Experience with storage platforms such as VAST Data, NetApp, Dell PowerScale, Pure Storage, or Ceph.

Familiarity with high-performance storage networking, including 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 high-performance computing environments.

Experience planning storage capacity, expanding storage systems, and supporting data migrations.

What Success Looks Like

Reliable compute and storage infrastructure, repeatable automation, faster problem resolution, effective capacity planning, and clear documentation that enables the team to operate and scale efficiently.

Why Join Cerebras

People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:

Build a breakthrough AI platform beyond the constraints of the GPU.

Publish and open source their cutting-edge AI research.

Work on one of the fastest AI supercomputers in the world.

Enjoy job stability with startup vitality.

Our simple, non-corporate work culture that respects individual beliefs.

Find out more about what it's like to work at Cerebras here !

Apply today and become part of the forefront of groundbreaking advancements in AI!

Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.

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