AI Infrastructure Operations Engineer

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 AI Infrastructure Operations Engineer (SiteOps) is an entry-level individual contributor role focused on the deployment, bring-up, monitoring, and first-line troubleshooting of Cerebras AI infrastructure in data center environments. The role supports CS systems, cluster server hardware, cluster networking hardware, and hardware telemetry and monitoring tools.

Support reliable operation and scale-out of Cerebras AI clusters by executing defined hardware bring-up and validation procedures, monitoring telemetry, performing first-line troubleshooting, and escalating issues using established workflows.

• Assist with deployment and bring-up of CS-X systems, cluster servers, and networking hardware
• Execute power-on sequencing, readiness checks, and validation tests
• Monitor hardware telemetry, alerts, and dashboards
• Perform first-line troubleshooting and structured escalation
• Collect logs, telemetry, and observations during incidents

• Participate in incident response under senior engineer guidance
• Use existing monitoring, telemetry, and incident tracking tools
• Provide feedback on tooling and process gaps

• Build working knowledge of Cerebras system architecture
• Learn cluster hardware and networking fundamentals
• Shadow senior engineers during complex debugging
• Progress toward independent ownership of defined workflows

• Bachelor’s degree in a relevant engineering field or equivalent experience
• 0–3 years experience in hardware operations, systems engineering, or datacenter environments
• Basic familiarity with server hardware, networking fundamentals, and Linux systems

• Internship or early-career experience in datacenter or hardware lab environments
• Exposure to monitoring or telemetry systems
• Comfort working in data centers