Senior Manager, Service Operations & Enablement
Cerebras
Senior Manager, Service Operations & Enablement
Cerebras
AI accelerator hardware replacing GPUs
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.
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.
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.
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.
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.
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.
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.
Partner with the Colocation/DC Contracts organization to evaluate the operational suitability of prospective data center environments.
Assess remote-hands capability, staffing and coverage, response SLAs, site access, receiving/logistics capability, spare-parts storage, escalation procedures, maintenance practices, incident response, serviceability, and operational support maturity.
Provide operational requirements and recommendations into the commercial contracting process while the Colo/DC Contracts organization retains commercial ownership.
Cerebras has a formal, repeatable Ready-for-Service process.
Technical Completion and Operational Acceptance are clearly differentiated.
New production environments have defined ownership, monitoring, escalation, procedures, and support models.
Cerebras and SiteOps operators have defined competency requirements.
Customer-operated deployments have standardized O&M models.
Training effectiveness is measured through competency rather than attendance.
Operational documentation is authoritative, current, and discoverable.
Time from technical completion to operational acceptance decreases.
Readiness-related early-life incidents decrease.
Customer and partner operators resolve a growing proportion of routine operational issues independently.
8+ years in infrastructure operations, service operations, technical enablement, customer infrastructure, production readiness, or related technical fields.
3+ years leading teams or significant technical programs.
Experience operationalizing complex hardware/software infrastructure.
Experience establishing service-transition or operational-readiness processes.
Strong understanding of production infrastructure operations and support models.
Experience developing technical training, competency, certification, or knowledge-management programs.
Strong customer-facing and cross-functional communication skills.
Ability to turn complex technical knowledge into scalable operational processes.
AI/HPC, large-scale compute, data center, cloud, or semiconductor systems experience.
Experience supporting customer on-premises infrastructure.
Experience developing O&M programs.
Experience building training/certification programs for complex technical systems.
Experience performing operational assessments of data center/service-provider environments.
We are looking for someone who thinks like an operator, communicates like a service leader, and teaches like an engineer - someone who creates standards without unnecessary bureaucracy and measures enablement through demonstrated operational capability.
Cerebras cannot scale globally if every deployment depends indefinitely on a small number of Cerebras experts. This role turns Cerebras operational knowledge into a repeatable capability that can travel with every cluster we deploy.
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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Cerebras Systems creates AI acceleration hardware and software. Its CS-2 system is designed to replace traditional GPU clusters for AI workloads, speeding up training and inference while simplifying the setup by eliminating the need for parallel programming, distributed training, and cluster management. The product works as a single, large processor-based accelerator with accompanying software and cloud services to run AI models efficiently, reducing latency and time to results. Compared with competitors, Cerebras differentiates itself with the largest processor in the industry and an integrated hardware-software stack that aims to streamline AI workflows rather than relying on multi-GPU clusters. The company's goal is to help research labs, healthcare, finance, and other industries achieve faster, more cost-effective AI development and deployment by offering a turnkey high-performance AI compute solution.
Explore more opportunities at Cerebras