Staff Site Reliability Engineer – Automation and Platform

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. Cerebras' current customers include top 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. Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, 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. About the Role We are building a high-performance SRE function to support one of the world’s fastest-growing AI inference services, powered by the Wafer-Scale Engine (WSE). This team will help deliver world-class, ultra-reliable inference infrastructure for l [... source excerpt omitted ...] -service delivery pipelines, shared observability common tooling. This role starts with ~1 month of hands-on operational immersion to gain deep familiarity with our current stack, production pain points, and high-stakes workflows. From there, your primary focus shifts to architecting and delivering the "tomorrow" layer: declarative GitOps-driven CD for model releases, capacity provisioning and cluster upgrades. Success over the first year in this role will be defined by enabling core teams, product managers, external customers, and cluster stakeholders to operate in a fully self-service model with strong reliability guarantees. You will partner with our early-career SRE sub-team, [... source excerpt omitted ...] joys turning complexity into elegant reliability at scale, this is your chance to lead this transformation from the front. This role does not require 24/7 on-call rotations. Key Responsibilities Define and implement a robust strategy for delivering and running software reliably and at scale across multiple datacenters and cloud-based solutions. Architect self-service platforms and internal tooling that let product teams, external customers, and cluster operators safely trigger and observe critical workflows with minimal handoffs. Define and evolve reliability practices for inference workloads, including SLOs and SLIs for latency, throughput, and accuracy stability; error budgets;