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 Role

As Cerebras infrastructure expands across colocation facilities and customer on-premises environments, successful installation is only the beginning. Every deployment must transition from technically complete to operationally ready, and the people responsible for operating it must have the knowledge, procedures, and capabilities required to do so successfully.

We are seeking a Senior Manager, Service Operations & Enablement to own this transition and build the operating capabilities required to support Cerebras infrastructure throughout its service lifecycle.

This leader will own Operational Readiness, On-Prem O&M, Operator Enablement, Training & Certification, and operational due diligence for new infrastructure environments.

Mission

Ensure every Cerebras deployment can successfully enter and remain in production by establishing operational readiness, enabling the people who operate it, and creating a repeatable O&M model across Cerebras-operated, partner-operated, and customer-operated environments.

Responsibilities

Own Operational Readiness

Define and maintain Cerebras Ready-for-Service requirements.

Own the operational acceptance process between Build & Deploy and production operations.

Establish Operational Readiness Reviews for new clusters and major changes.

Ensure monitoring, alerting, runbooks, escalation, support, spares, maintenance, and operator-readiness requirements are satisfied.

Identify readiness gaps and drive them to closure.

Measure Technical Completion to Operational Acceptance performance.

Analyze early-life production issues and improve readiness criteria accordingly.

Build the On-Prem O&M Model

Define scalable O&M models for customer on-premises deployments.

Establish responsibilities for Cerebras-managed, jointly operated, and customer-operated environments.

Define L1/L2/L3 operational boundaries and escalation paths.

Establish maintenance, support, service, and operating procedures.

Ensure each deployment has a clearly documented operational ownership model.

Develop mechanisms that allow customer environments to become increasingly operationally independent where appropriate.

Own Learning, Training & Certification

Build the training and competency framework for people operating Cerebras infrastructure.

Develop training for Central Ops, SiteOps/DC Ops technicians, partners, and customer operators.

Establish role-based curricula covering Cerebras systems, cluster operation, monitoring, troubleshooting, maintenance, escalation, and recovery.

Establish operator qualification/certification standards.

Maintain competency matrices defining which activities operators are qualified to perform.

Develop refresher training and requalification mechanisms.

Create practical drills and simulations for critical operational scenarios.

Own Operational Knowledge

Establish the operational knowledge-management framework.

Own standards and lifecycle management for runbooks, SOPs, troubleshooting procedures, and operational playbooks.

Translate Engineering knowledge into repeatable operational procedures.

Ensure incident and reliability learnings are incorporated into procedures and training.

Reduce dependence on tribal knowledge and individual Cerebras experts.

New DC Operational Due Diligence

Partner with the Colocation/DC Contracts organization to evaluate the operational suitability of prospective data center environments.