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.

Requirements

  • 7+ years of professional experience in software engineering, infrastructure engineering, DevOps, developer productivity, or a related area.
  • Deep hands-on experience with CI/CD systems and building or evolving automated build, test, and deployment infrastructure.
  • Experience with artifact repositories, software packaging, dependency management, and reproducible build concepts.
  • Experience with cloud computing platforms, with AWS preferred, and programmatic infrastructure provisioning.
  • Strong experience with distributed version control systems, code review workflows, branching strategies, and repository management.
  • Strong understanding of Linux/Unix systems, networking fundamentals, and scripting or programming for automation.
  • Experience with containerization and container orchestration, with Kubernetes preferred.
  • Strong troubleshooting skills and the ability to debug complex distributed systems and infrastructure issues.
  • Demonstrated experience leading technical initiatives across multiple teams and driving improvements to developer infrastructure at organizational scale.
  • Ability to identify architectural bottlenecks, evaluate tradeoffs, and drive long-term improvements rather than only addressing operational issues.
  • Experience operating production systems and participating in on-call, incident response, and postmortem processes.

Nice To Haves

  • Experience with infrastructure-as-code tools and practices.
  • Proficiency in Python, Go, Shell, or another language used for infrastructure automation and developer tooling.
  • Experience with build systems, build graph optimization, or large-scale build infrastructure.
  • Experience with observability practices including monitoring, logging, alerting, and performance analysis.
  • Experience building internal developer platforms, self-service tooling, or developer-facing infrastructure.
  • Experience applying AI/LLM tooling to engineering workflows or developer productivity.
  • BS/MS in Computer Science or a related field, or equivalent practical experience.

Responsibilities

  • Design, build, and evolve CI/CD pipelines that support reliable and efficient build, test, and release workflows across the organization.
  • Own and improve artifact lifecycle systems, including versioning, storage, distribution, dependency management, and reproducible builds at scale.
  • Partner with development teams to design and improve code review workflows, branching strategies, and automated integration processes.
  • Provision, monitor, and optimize cloud infrastructure supporting CI workloads, balancing cost, performance, scalability, and reliability.
  • Troubleshoot complex build failures, pipeline bottlenecks, and infrastructure issues, driving root-cause analysis and implementing durable fixes.
  • Design and drive improvements to internal build infrastructure, test infrastructure, developer tooling, and automation that increase developer velocity and engineering productivity.
  • Identify systemic bottlenecks across developer workflows and lead architectural improvements to developer infrastructure.
  • Contribute to the company’s efforts around AI tooling to improve engineering productivity and automate repetitive workflows.
  • Provide technical leadership across projects, influence engineering standards, and mentor other engineers within the Developer Productivity organization.
  • Participate in on-call and incident response for Developer Productivity systems and services.

Benefits

  • Job stability with startup vitality
  • Simple, non-corporate work culture that respects individual beliefs
  • Continuous learning, growth and support of those around them
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