---
title: 'Infrastructure Systems Engineer – Linux, Storage & Automation at Cerebras Systems'
canonical: 'https://feeny.ai/job/infrastructure-systems-engineer-linux-storage-automation-cerebras-systems-x09zpw8fb6q2'
type: 'job'
last_seen: '2026-10-20'
---

# Infrastructure Systems Engineer – Linux, Storage & Automation at Cerebras Systems

- **Company:** [Cerebras Systems](https://feeny.ai/companies/cerebras-systems)
- **Location:** Sunnyvale, CA
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-10-19
- **Last confirmed live:** 2026-10-20
- **Apply:** https://jobs.ashbyhq.com/cerebras/dbb21f89-1e93-4142-99da-8fe7c5d62e8b

## Job 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](https://openai.com/index/cerebras-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](https://www.cerebras.ai/join-us)! 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. This website or its third-party tools process personal data. For more details, click [here](https://www.cerebras.net/privacy/) to review our CCPA disclosure notice.

## About Cerebras Systems

## Company Overview
- **One-liner**: Cerebras builds wafer-scale AI chips (the largest semiconductors ever made) and supercomputers that deliver up to 15x faster inference than GPUs, offered both on-premises and via cloud APIs.
- **Entity Type**: Public (NASDAQ: CBRS) — filed for IPO and now listed on the Nasdaq.
- **Headquarters**: Sunnyvale, California, United States
- **Founded**: 2015
- **Founders**: Andrew Feldman, Gary Lauterbach, Michael James, Sean Lie, Jean-Philippe Fricker

## Core Business
- **Primary industries**: Semiconductor manufacturing, AI computing hardware and software, cloud AI services.
- **Target customers**: B2B – enterprises, government research labs, cloud service providers, and AI developers.
- **Mission**: “Building impossible technologies so you can too” – accelerating AI through wafer-scale computing.

## Products & Services
- **Wafer-Scale Engine (WSE-3)**: The world’s largest AI chip (215 mm²), 58x larger than a typical GPU, built for ultra‑fast AI training and inference. Manufactured by TSMC.
- **CS-3 Supercomputer**: A single system powered by the WSE-3, delivering record-breaking AI performance for on-premises deployment.
- **Cerebras AI Inference Cloud & Training Cloud**: Pay-as-you‑go APIs that provide drop‑in OpenAI‑compatible access to Cerebras’ hardware for serving, fine‑tuning, and pre‑training models.
- **Condor Galaxy Network**: A series of supercomputers (e.g., CG‑1 with 4 exaFLOPs) built in partnership with G42 for high‑performance AI.

## Market Standing
- **Valuation/Market Cap**: Not disclosed (recently public; market cap data not available in provided sources).
- **Key Metric**: Annual revenue of $78.7 M (latest); total funding of $2.7 B across 15 rounds.
- **Notable Investors/Partners**: G42, OpenAI (signed in 2026), Amazon Web Services (signed in 2026), Meta (Llama API), Perplexity, Mistral, Hugging Face, OpenRouter.
- **Growth Signals**: 
  - 34.3% YoY headcount growth (701 employees).
  - Rapid data center expansion across North America and Europe.
  - Won the HPCwire Readers’ & Editors’ Choice 2025 for Best AI Product/Technology.
  - Named to Forbes America’s Best Startup Employers 2026 and Fast Company Most Innovative Companies 2026 (AI).

## Competitive Advantages
- **Wafer‑scale architecture**: Eliminates interconnect bottlenecks, reducing latency and delivering up to 15x faster inference than GPU clusters.
- **Largest AI chip ever built**: 58x larger than any GPU, enabling massive on‑chip memory (SRAM) and compute density.
- **Full‑stack offering**: Hardware + cloud APIs + on‑prem systems, giving customers deployment flexibility.
- **Strong customer relationships**: Key contracts with OpenAI, AWS, G42, and Mayo Clinic (2024 Gordon Bell Prize work).

## Strategic Focus
- **Scale inference capacity**: Building out data centers to become the world’s #1 provider of high‑speed AI inference.
- **Deepen cloud partnerships**: Expanding pay‑as‑you‑go cloud access and enterprise deployments.
- **Advance wafer‑scale technology**: Continuous R&D on WSE‑3 successors and software stack (compiler, ML workflows).
- **Broaden model support**: Already serving Llama, Gemma, Qwen, Mistral, and more; integrating with Hugging Face and OpenRouter.

## Why Work Here
- **Culture**: “Extraordinary people, breakthrough innovation, global impact” – the company highlights collaborative, low‑overhead teams with little bureaucracy.
- **Work environment**: Hybrid/office with locations in Sunnyvale, San Diego, Toronto, and Bangalore. Inclusive and flexible policy.
- **Perks**: Premium medical/dental/vision, life insurance, generous vacation, 401(k) and Group RRSP retirement plans, daily catered meals, healthy snacks, family‑friendly events (including CEO’s famous BBQ).
- **Engineering focus**: Tackling fundamental challenges in chip design, system software, compiler technology, and ML workflows. Positions range from hardware (Design Verification, Manufacturing) to software (SRE, Compiler, Cloud).
- **Philanthrophy**: Supports local communities and hosts students from around the world for Q&A.

## Sources
1. [cerebras.ai/company](https://www.cerebras.ai/company)
2. [cerebras.ai](https://www.cerebras.ai/)
3. [cerebras.ai/join-us](https://www.cerebras.ai/join-us)
4. [linkedin.com/company/cerebras-systems](https://www.linkedin.com/company/cerebras-systems)

## Other roles at Cerebras Systems

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- [Senior Manager, Service Operations & Enablement](https://feeny.ai/job/senior-manager-service-operations-enablement-cerebras-systems-sunnyvale-qmxx1hpzvnvq) — Sunnyvale, CA
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- [Senior Manager, Production & Fleet Operations](https://feeny.ai/job/senior-manager-production-fleet-operations-cerebras-systems-sunnyvale-tnzs6bz9xfma) — Sunnyvale, CA
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