AI Fleet Platform Software Engineer

Cerebras Systems•Sunnyvale, CA

1d•Hybrid

About The Position

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. 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.

Requirements

12+ years of industry experience building and operating production software for distributed systems or large-scale infrastructure.
Strong Go or Python skills and experience designing services and APIs.
Expertise in control planes, fleet management systems, or operational platforms.
Experience with Linux, containers, Kubernetes, and handling failures across distributed systems.
Experience designing systems that handle asynchronous work, retries, and partial failures.
Experience with event streaming, workflow automation, or time-series telemetry.
Strong judgment in reliability, security, and observability.
Ability to lead ambiguous projects and work effectively across engineering and operations teams.

Nice To Haves

Building software for incident response, hardware health, or capacity management.
Developing dashboards and applications for infrastructure operators.
Working with AI clusters and their compute, networking, and hardware systems.

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.