Software Engineer, Cluster Deployment
Cerebras is hiring a Software Engineer, Cluster Deployment for a remote role open to applicants in United States. Level rates it ; you can apply on Cerebras.
Level's read on this job
- Works on AI ●●●○ is how Level rates this software engineer role: the daily work is on AI products, without building the model.
- This is listed as a remote role.
- The posting mentions OpenAI, Python and Bash among its tools and skills.
- Level classes it as a mid-level role.
- Cerebras has 121 other open roles on Level.
AI in this role
Build and operate software automation systems that deploy, validate, and manage AI compute clusters across global data centers.
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.
About the Role
We build and operate the software systems that deploy, validate, and manage AI compute clusters across data centers worldwide for the world’s fastest AI Inference. Our work turns complex bare-metal infrastructure into repeatable, automated deployment flows spanning server provisioning, network configuration, Kubernetes bring-up, health validation, and operational handoff.
As a Software Engineer on the Cluster Deployment Automation team, you will help build the pushbutton tooling that makes large-scale cluster deployments faster, safer, and more reproducible. This role is designed for talented engineers passionate about learning through hands-on work with Python, Bash, Ansible, Linux, bare-metal servers, networking equipment, Kubernetes, and observability systems while learning how production AI infrastructure is built and operated at scale.
Responsibilities
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.
Basic 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.
Preferred Qualifications
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.
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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How we rate this
Software Engineer, Cluster Deployment at Cerebras rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Pay
- Typical software engineer job
- $168k
This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs
Questions you could be asked
- Tell me about a research question you investigated. What did you find?
- Tell me about a project where infrastructure as code was part of your work. What did you do?
- Tell me about a project where gitops was part of your work. What did you do?
- Tell me about a project where cluster deployment was part of your work. What did you do?
- Tell me about a project where automation was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI Research, Infrastructure As Code, Gitops, Cluster Deployment, and Automation. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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