Staff Site Reliability Engineer – Automation and Platform
Cerebras · Sunnyvale, CA
About this role
## About the Role Cerebras Systems is 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). As a **Staff Site Reliability Engineer (Automation and Platform)**, you’ll lead efforts to eliminate toil at scale by building **self-service delivery pipelines** and **shared observability tooling**. This role begins with ~**1 month of hands-on operational immersion** to learn the current stack, production pain points, and high-stakes workflows. After that, your primary focus shifts to architecting and delivering the “tomorrow” layer: **declarative, GitOps-driven CD for model releases**, plus **capacity provisioning** and **cluster upgrades**. Success in your first year means enabling core teams, product managers, external customers, and cluster stakeholders to operate with **fully self-service workflows** and **strong reliability guarantees**. You’ll partner with an early-career SRE sub-team to automate their toil and mentor them as platform engineers. **On-call:** 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 so product teams, external customers, and cluster operators can safely trigger and observe critical workflows with minimal handoffs. - Define and evolve reliability practices for inference workloads, including: - **SLOs/SLIs** for latency, throughput, and accuracy stability - **Error budgets** - **Blameless postmortems** - **Chaos testing** - **Capacity forecasting** across multi-datacenter and on-prem environments - Mentor mid-level SREs, support critical incident escalations, and prioritize high-leverage automation based on production pain points. - Drive measurable impact using metrics such as **toil reduction**, **deployment velocity**, **SLO compliance**, **MTTR**, and adoption of self-service workflows. --- ## Required Experience & Skills - **8+ years** in SRE, infrastructure engineering, or platform engineering, with a strong record of improving automation and reliability at large scale in FAANG, hyperscaler, or similarly demanding environments. - Deep expertise operating **large-scale heterogeneous clusters** with a proprietary cloud control plane. - Proven track record designing and delivering **CI/CD or GitOps** systems using **Argo CD** or similar tools, with strong safety and observability. - Hands-on experience with observability systems such as **Loki, Tempo, Mimir, and Prometheus**. - Ability to lead complex end-to-end projects, influence cross-functional stakeholders, and communicate technical direction clearly. --- ## Nice-to-Haves - Experience with **Bazel** or other large-scale build systems in production. - Background in **AI/ML inference systems**, including model serving runtimes, GPU/wafer-scale orchestration, latency & accuracy SLOs, or drift monitoring. - Prior work on **predictive autoscaling**, **chaos engineering**, or **cost-aware capacity planning** for compute-intensive workloads. --- ## Location - **SF Bay Area** - **Toronto** --- ## Why Join Cerebras People who are serious about software make their own hardware. Cerebras is building a breakthrough architecture that’s unlocking new opportunities for the AI industry—backed by rapid growth and freq
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