Site Reliability Engineer - Ops & Automation
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Key skills for this role
Role Overview
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), helping deliver infrastructure for frontier-class models from leading model builders such as OpenAI.
This role offers immediate ownership of real production systems at a growing scale, direct mentorship from seasoned engineers, and close collaboration with incoming Staff SREs who will focus on long-term automation.
After ~1 month of shared hands-on operations with the Staff engineers, you’ll primarily operate the current setup, bring up new capacity in high-stakes environments and help bring new continuous delivery pipelines into production use.
If you thrive in high-ownership SRE roles at scale and want to help shape a team from the ground up in cutting-edge AI Inference infrastructure, this is your chance.
This role does not require 24/7 on-call rotations.
Key Skills for This Role
Full Job Posting
Key Responsibilities
- Remain hands-on with operational execution (releases, capacity changes, cluster upgrades) over the next year as we build robust continuous delivery pipelines and self-service capabilities
- Contribute to the development of self-service CD pipelines for key workflows using our stack: Kubernetes, Bazel, Prometheus/Grafana/InfluxDB, Python, and Go.
- Build reusable automation and internal developer tools that minimize operational toil and cross-team friction
- Develop and extend telemetry, observability and alerting solutions to ensure operational reliability at scale
- Collaborate with Cluster Ops and development teams to identify high-impact automation opportunities and iterate quickly
- Contribute to reliability practices (SLOs, post-mortems, capacity planning)
Required Experience & Skills
- 2-4+ years in SRE with a strong operations or automation focus
- Production Kubernetes experience
- Solid Python or Go for building tools and automation
- Proficiency with Prometheus, Grafana, and observability-driven workflows
- Ability to measure and communicate impact – reliability metrics, operational toil, velocity gains
Nice-to-Have
Hands-on GitOps expertise, Argo CD / Flux or equivalent, is a plus
Experience with building continuous delivery pipelines is a strong plus
Experience with Bazel or similar build systems is a strong plus.
Familiarity with capacity planning, on-prem or multi-datacenter environments
Location
SF Bay Area
Toronto
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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About Cerebras Systems
Designs processors and systems for AI training and inference.
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