Software Engineer - Tools & Infrastructure / DevOps

About the role

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 https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.

Responsibilities:

- Contribute to the development and maintenance of CICD pipelines, ensuring reliable and efficient build, test, and release workflows across the organization.

- Help manage artifact lifecycle systems including versioning, storage, distribution, and dependency management to support 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 to support CI workloads, balancing cost efficiency with performance and reliability.

- Troubleshoot build failures, pipeline bottlenecks, and infrastructure issues, driving root-cause analysis and implementing lasting fixes.

- Contribute to internal build infrastructure, test infrastructure, tooling, and automation that improves developer velocity and engineering productivity.

- Contribute to the company’s efforts on AI tooling to boost engineering productivity efficiently.

Skills & Qualifications

- 4-8 years of professional experience in a DevOps, infrastructure, or software engineering role.

- Familiarity with CICD systems and hands-on experiences in building or maintaining automated build and deployment pipelines.

- Understanding of artifact repository management and software packaging concepts.

- Experience with cloud computing platforms (AWS preferred) and programmatic resource provisioning.

- Proficiency with distributed version control systems, code review processes, and repository management.

- Foundational knowledge of operating system concepts (Linux/Unix), networking fundamentals, and scripting for automation.

- Experience with containerization and container orchestration (Kubernetes preferred).

- Strong troubleshooting skills and a methodical approach to debugging distributed systems.

- Curiosity about how large-scale infrastructure is built, operated, and improved.

- Being part of oncall and incident response task force of Dev Productivity org.

Preferred Skills & Qualifications