{"id":2869391,"url":"https://alion.io/job/cerebras-systems-infrastructure-systems-engineer-linux-storage-automation","title":"Infrastructure Systems Engineer – Linux, Storage & Automation","company":{"id":31,"name":"Cerebras Systems","domain":"cerebras.ai","url":"https://alion.io/company/cerebras-systems","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":76,"open_postings":25,"ghost_share":0,"stale_share":0.76,"repost_share":0,"time_to_fill_p50_days":93,"computed_at":"2026-10-22T06:10:10Z"}},"role":"DevOps","role_family":"DevOps","seniority":null,"employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Sunnyvale, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":147000,"max_usd":325000,"period":"year","method":"role_country_seniority_unknown","sample_n":4161},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon S3","optional":false},{"name":"Ansible","optional":false},{"name":"Bash","optional":false},{"name":"Cerebras","optional":false},{"name":"Configuration Management","optional":false},{"name":"DHCP","optional":false},{"name":"DNS","optional":false},{"name":"Git","optional":false},{"name":"KVM","optional":false},{"name":"Linux","optional":false},{"name":"OpenAI","optional":false},{"name":"Proxmox VE","optional":false},{"name":"Python","optional":false},{"name":"TCP/IP","optional":false},{"name":"VMWare","optional":false},{"name":"Docker","optional":true},{"name":"InfiniBand","optional":true},{"name":"Kubernetes","optional":true}],"status":"live","first_seen_at":"2026-10-19T18:24:37Z","employer_posted_date":"2026-10-19","last_verified_at":"2026-10-22T15:46:01Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"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. \nThis 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.\nCerebras 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.\nThe Role\nWe 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.\nResponsibilities\nDeploy, configure, and maintain Linux servers across physical and virtual environments.\n\nDeploy and support data storage systems, including block, file, and object storage.\n\nConfigure and troubleshoot storage connectivity, volumes, filesystems, permissions, and access from Linux hosts and virtual machines.\n\nMonitor storage capacity, performance, and availability; investigate latency, throughput, and connectivity issues.\n\nDevelop Python and Bash scripts to automate provisioning, configuration, validation, and routine operational tasks.\n\nBuild and maintain Ansible playbooks and roles for consistent, repeatable infrastructure deployments.\n\nTroubleshoot issues across operating systems, applications, networking, storage, and virtualization platforms.\n\nInvestigate logs, analyze system behavior, and resolve performance, availability, and configuration problems.\n\nManage virtual machines and troubleshoot hypervisor, virtual networking, and storage integration issues.\n\nSupport server provisioning, operating system installation, patching, upgrades, and configuration management.\n\nSupport data protection and recovery through snapshots, replication, backups, and restore validation.\n\nImplement monitoring, health checks, and alerts to identify problems early.\n\nCollaborate with engineering, networking, storage vendors, and data center operations teams to deploy and support infrastructure.\n\nDocument configurations, troubleshooting procedures, and operational runbooks.\n\nQualifications\nStrong hands-on experience administering and troubleshooting Linux systems.\n\nProficiency in Python and shell scripting, particularly Bash.\n\nPractical experience with Ansible for automation and configuration management.\n\nExperience with virtualization platforms such as KVM, VMware, or Proxmox.\n\nHands-on experience administering enterprise or distributed storage systems.\n\nWorking knowledge of block, file, and object storage concepts, with practical experience in protocols such as NFS, SMB, iSCSI, or S3.\n\nFamiliarity with Linux storage management, including disk configuration, RAID, LVM, filesystems, and mount management.\n\nAbility to troubleshoot storage performance using metrics such as IOPS, throughput, and latency.\n\nStrong debugging skills and a methodical approach to root cause analysis.\n\nWorking knowledge of TCP/IP, DNS, DHCP, routing, VLANs, and network troubleshooting.\n\nFamiliarity with Linux services, permissions, processes, package management, and system logs.\n\nExperience using Git for version control and collaborative development.\n\nAbility to own technical problems through resolution and communicate findings clearly.\n\nPreferred Qualifications\nExperience with storage platforms such as VAST Data, NetApp, Dell PowerScale, Pure Storage, or Ceph.\n\nFamiliarity with high-performance storage networking, including RDMA, RoCE, or InfiniBand.\n\nExperience with bare-metal provisioning, PXE boot, Kickstart, or cloud-init.\n\nFamiliarity with server management interfaces such as BMC, IPMI, or Redfish.\n\nExperience with Docker, Kubernetes, or other container technologies.\n\nFamiliarity with infrastructure monitoring and centralized logging tools.\n\nExperience supporting data center, AI/ML, or high-performance computing environments.\n\nExperience planning storage capacity, expanding storage systems, and supporting data migrations.\n\nWhat Success Looks Like\nReliable compute and storage infrastructure, repeatable automation, faster problem resolution, effective capacity planning, and clear documentation that enables the team to operate and scale efficiently.\nWhy Join Cerebras\nPeople 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:\nBuild a breakthrough AI platform beyond the constraints of the GPU.\n\nPublish and open source their cutting-edge AI research.\n\nWork on one of the fastest AI supercomputers in the world.\n\nEnjoy job stability with startup vitality.\n\nOur simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here!\nApply today and become part of the forefront of groundbreaking advancements in AI!\nCerebras 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.\nThis website or its third-party tools process personal data. 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