Level

Cerebras

AI Fleet Platform Software Engineer

AI in this role

Build and operate large-scale software platforms and control planes for managing AI cluster infrastructure and compute fleets.

openaigopythonlinuxkubernetes
ai-researchdistributed-systemsinfrastructurefleet-managementcontrol-planes

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.

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 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.

Preferred Experience

  • 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.

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!

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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How we rate this

AI Fleet Platform Software Engineer at Cerebras rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

AI ResearchDistributed SystemsInfrastructureFleet ManagementControl PlanesOpenAIGoPython

Questions you could be asked

  1. Tell me about a research question you investigated. What did you find?
  2. Tell me about a project where distributed systems was part of your work. What did you do?
  3. Tell me about a project where infrastructure was part of your work. What did you do?
  4. Tell me about a project where fleet management was part of your work. What did you do?
  5. Tell me about a project where control planes was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: AI Research, Distributed Systems, Infrastructure, Fleet Management, and Control Planes. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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