Software Engineer

Build and maintain CI/CD pipelines, artifact management, cloud infrastructure, and developer productivity tooling at Cerebras to accelerate AI hardware and software engineering. Requires 2-5 years DevOps/infrastructure experience, Kubernetes, AWS, and strong troubleshooting skills.

About the job

Responsibilities

Contribute to the development and maintenance of CI/CD 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.
Be part of oncall and incident response task force of Dev Productivity org.

Requirements

2-5 years of professional experience in a DevOps, infrastructure, or software engineering role.
Familiarity with CI/CD systems and hands-on experience 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.

Preferred Skills

Familiarity with infrastructure-as-code tools and practices.
Scripting proficiency in Python or Shell for build automation and tooling.
Exposure to build systems and build graph optimization.
Understanding of observability practices including monitoring, logging, and alerting.
BS/MS in Computer Science or a related field, or equivalent practical experience.