Software Engineer, Cluster Deployment

The role

You will build and operate software systems to deploy, validate, and manage AI compute clusters across data centers. You will develop automation for deployment workflows and turn manual steps into repeatable pushbutton workflows.

What you will do

• Develop and maintain automation for deployment workflows, including provisioning, configuration, validation, and operational handoff.
• Turn manual deployment steps into tested, repeatable pushbutton workflows.
• Participate in hands-on cluster deployments to build practical debugging and operational expertise.
• Troubleshoot issues across Linux systems, bare-metal servers, networking, storage, Kubernetes, and connectivity.
• Contribute to infrastructure-as-code and GitOps workflows using tools such as Terraform, Ansible, pull requests, and code review.
• Add health checks, observability, dashboards, and validation logic to improve deployment reliability.
• Partner with networking, infrastructure, security, and operations teams to deliver secure and reproducible data center deployments.

Required qualifications

• 2+ years of mid- to large-scale data center deployment
• Strong fundamentals in Python and Bash, with the ability to write scripts and small programs.
• Basic Linux experience, including command-line usage, processes, filesystems, and disk troubleshooting.
• Working knowledge of Git, including branching, commits, pull requests, and code review.
• CS, ECE, or related technical degree, or equivalent practical experience.
• Curiosity, strong problem-solving instincts, and willingness to work hands-on with real infrastructure.

Nice to have

• Networking fundamentals, including VLANs and routing basics; exposure to BGP, switch configuration, or Arista EOS automation is a plus.
• Kubernetes experience or familiarity.
• Infrastructure-as-code and GitOps experience, including Terraform, Ansible, and PR-based change control.
• Bare-metal provisioning concepts such as PXE, DHCP, iPXE, Redfish, IPMI, and BMC management.
• Observability experience with Prometheus or Grafana.
• API design and client-server architecture.
• Automation side projects or open-source contributions.

Benefits

• 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.

About the company

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. The company works with leading model labs, global enterprises, and cutting-edge AI-native startups.