Job description

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 openai.com with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. THE ROLE Cerebras operates AI clusters across a growing number of data centers. As the fleet expands, the software used to monitor and manage it must scale with it. We are seeking a senior software engineer to build the platforms and tools that help our teams understand fleet health, respond to issues, and keep compute capacity available. You will own substantial engineering work across backend services, operational tools, and user-facing applications. You will partner with Cluster Operations, infrastructure, inference, security, and data center teams to turn real operational challenges into software that works reliably at scale. RESPONSIBILITIES - Build and operate software for managing large fleets of AI clusters - Give operators clear, actionable views of cluster health, capacity, performance, and ongoing issues. - Develop services and integrations that bring together data and workflows from multiple infrastructure systems. - Automate repetitive work and improve the tools teams use to investigate incidents and restore service. - Design systems that remain reliable as the fleet grows and continue to function through component and site failures. - Work closely with users of the platform to understand their needs and make practical product and engineering decisions. - Lead projects from initial design to production, measure their impact, and use operational feedback to guide improvements. SKILLS AND REQUIREMENTS - 12+ years of industry experience building and operating production distributed systems or large-scale infrastructure software. - Strong Go skills. You will work with Go, Protocol Buffers, and SQL regularly. Python experience is an added benefit. - Experience building control planes, fleet management systems, or operational platforms. - Experience designing APIs and data models that serve multiple consumers, with a considered approach to versioning and compatibility. - Experience building asynchronous systems that support idempotency, concurrency, and reconciliation while preventing unintended state drift. - A strong testing practice, especially for software that can change the state of running production clusters. - Experience with Linux, containers, and Kubernetes. - Experience with durable workflow execution, event streaming, or time-series telemetry at high cardinality. - Sound judgment about reliability, security, and observability, including how a system behaves when its dependencies are unavailable. - Ability to take an ambiguous problem from design through production and improve the solution using operational feedback. PREFERRED EXPERIENCE - Building infrastructure software for thousands of hosts across multiple sites. - Developing software for incident response, hardware health, or capacity management. - Deploying and operating services on AWS. - Working with AI or HPC clusters and their compute, networking, and hardware systems. - Developing dashboards or applications for infrastructure operators. LOCATION - SF Bay Area. - Toronto, Canada. 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: 1. Build a breakthrough AI platform beyond the constraints of the GPU. 2. Publish and open source their cutting-edge AI research. 3. Work on one of the fastest AI supercomputers in the world. 4. Enjoy job stability with startup vitality. 5. Our simple, non-corporate work culture that respects individual beliefs. Find out more about what it's like to work at Cerebras here cerebras.ai! 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. This website or its third-party tools process personal data. For more details, click here cerebras.net to review our CCPA disclosure notice.

Requirements

Must-haves

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.
Build and operate software for managing large fleets of AI clusters
Give operators clear, actionable views of cluster health, capacity, performance, and ongoing issues.
Develop services and integrations that bring together data and workflows from multiple infrastructure systems.
Automate repetitive work and improve the tools teams use to investigate incidents and restore service.
Design systems that remain reliable as the fleet grows and continue to function through component and site failures.
Work closely with users of the platform to understand their needs and make practical product and engineering decisions.
Lead projects from initial design to production, measure their impact, and use operational feedback to guide improvements.
12+ years of industry experience building and operating production distributed systems or large-scale infrastructure software.
Strong Go skills. You will work with Go, Protocol Buffers, and SQL regularly. Python experience is an added benefit.
Experience building control planes, fleet management systems, or operational platforms.
Experience designing APIs and data models that serve multiple consumers, with a considered approach to versioning and compatibility.
Experience building asynchronous systems that support idempotency, concurrency, and reconciliation while preventing unintended state drift.
A strong testing practice, especially for software that can change the state of running production clusters.
Experience with Linux, containers, and Kubernetes.
Experience with durable workflow execution, event streaming, or time-series telemetry at high cardinality.
Sound judgment about reliability, security, and observability, including how a system behaves when its dependencies are unavailable.
Ability to take an ambiguous problem from design through production and improve the solution using operational feedback.
SF Bay Area.

Nice-to-haves

Building infrastructure software for thousands of hosts across multiple sites.
Developing software for incident response, hardware health, or capacity management.
Deploying and operating services on AWS.
Working with AI or HPC clusters and their compute, networking, and hardware systems.
Developing dashboards or applications for infrastructure operators.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aidesign systemsgosqlpythonkubernetesaws

Platform: ashby
Effort: quick