Level

Cerebras

AI Inference Core - Senior Senior Software Engineer for DevOps

Cerebras is hiring an AI Inference Core - Senior Senior Software Engineer for DevOps for a remote role open to applicants in United States. Level rates it ; you can apply on Cerebras.

Level's read on this job

  • Works on AI ●●●○ is how Level rates this software engineer role: the daily work is on AI products, without building the model.
  • This is listed as a remote role.
  • The posting mentions OpenAI and AI research among its tools and skills.
  • Level classes it as a senior role.
  • Cerebras has 121 other open roles on Level.

AI in this role

openai
ai-research

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.

About the Team

The Core Infrastructure team builds the software systems that power engineering workflows across Cerebras.

Our infrastructure coordinates complex work across machines, clusters, development environments, and hardware systems. We build orchestration frameworks, execution engines, scheduling systems, test infrastructure, developer tools, and reusable software platforms that allow engineers to build, test, qualify, and deliver software reliably at scale.

These systems are primarily built in Python, but the work goes far beyond scripting or automation. Our frameworks act as the control plane for distributed workflows, managing resources, execution state, concurrency, failures, retries, dependencies, and observability across large and complex environments.

About the Role

We are hiring a Software Engineer to build and operate the platform layer behind Cerebras engineering infrastructure.

You will work on CI/CD systems, Kubernetes, deployment automation, cloud and on-premises infrastructure, developer environments, artifact management, and observability. You will help make the systems engineers depend on reliable, scalable, and easy to operate.

This is an engineering-focused infrastructure role rather than a primarily ticket-driven operations position. You will automate repeated work, debug failures across system boundaries, and turn operational problems into durable software and platform improvements.

We value strong systems fundamentals, independent problem solving, and sound engineering judgment more than familiarity with any particular infrastructure product.

Responsibilities

  • Design, build, and maintain CI/CD systems supporting build, test, integration, qualification, and release workflows.

  • Build and operate Kubernetes-based platforms and services used by engineering teams across Cerebras.

  • Develop deployment systems, internal tools, and self-service workflows that make infrastructure changes repeatable, reviewable, and safe.

  • Improve infrastructure reliability, capacity, performance, cost efficiency, monitoring, and operational readiness.

  • Debug issues spanning CI pipelines, Kubernetes workloads, networking, storage, authentication, operating systems, and distributed applications.

  • Perform root-cause analysis and implement lasting fixes rather than relying on repeated manual intervention.

  • Partner with software, IT, security, networking, release, and developer-productivity teams to deliver scalable infrastructure solutions.

Skills & Qualifications

  • 5+ years of professional experience in platform engineering, DevOps, infrastructure engineering, site reliability engineering, or software engineering.

  • Hands-on experience building or maintaining CI/CD pipelines and automated software-delivery workflows.

  • Experience deploying and operating services using Kubernetes and containerized environments.

  • Experience with a major cloud platform, preferably AWS, and programmatic infrastructure provisioning.

  • Strong understanding of Linux or Unix operating-system fundamentals.

  • Understanding of networking concepts such as DNS, routing, load balancing, proxies, ports, TLS, and service connectivity.

  • Proficiency in Python, Shell, or another language used to build infrastructure automation and operational tooling.

  • Experience with monitoring, logging, alerting, dashboards, and incident investigation.

  • Strong debugging and problem-solving skills, including the ability to investigate issues spanning applications, infrastructure, networking, and operating systems.

Preferred Skills & Qualifications

  • Experience with infrastructure-as-code tools, specifically Terraform.

  • Experience with Kubernetes controllers, operators, custom resources, Helm, Argo CD, or similar platform technologies.

  • Experience managing artifact repositories, package registries, build caches, or software-distribution infrastructure.

  • Familiarity with build systems, dependency management, and reproducible-build practices.

  • Experience supporting hybrid environments spanning cloud infrastructure, on-premises systems, and specialized hardware.

  • Experience with identity and access management, secrets, certificates, TLS, or mTLS.

  • Experience building internal developer platforms or self-service infrastructure products.

  • BS/MS in Computer Science or a related field, or equivalent practical experience.

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.

This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.

How we rate this

AI Inference Core - Senior Senior Software Engineer for DevOps at Cerebras rates 67 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. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI ResearchOpenAI

Also common in software engineer jobs at this level

Pay

Typical software engineer job
$168k

This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs

Questions you could be asked

  1. Tell me about a research question you investigated. What did you find?
  2. Walk me through how you've used OpenAI in your day-to-day work.
  3. Describe a typical day in a role like this one: which parts run through AI directly?
  4. If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

  • List these exact terms on your resume: AI Research and OpenAI. 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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