Software Engineer - Tools & Infrastructure / DevOps

The role

This person will develop and maintain CICD pipelines and manage artifact lifecycle systems. They will also provision cloud infrastructure and contribute to internal build and AI tooling to improve developer velocity.

What you will do

• Contribute to the development and maintenance of CICD pipelines.
• Help manage artifact lifecycle systems including versioning, storage, distribution, and dependency management.
• 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.
• Troubleshoot build failures, pipeline bottlenecks, and infrastructure issues.
• Contribute to internal build infrastructure, test infrastructure, tooling, and automation.
• Contribute to the company's efforts on AI tooling to boost engineering productivity.
• Be part of oncall and incident response task force of Dev Productivity org.

Required 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.
• 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.
• Strong troubleshooting skills and a methodical approach to debugging distributed systems.
• Curiosity about how large-scale infrastructure is built, operated, and improved.

Nice to have

• AWS preferred
• Kubernetes preferred
• 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.

Benefits

• Build a breakthrough AI platform beyond the constraints of the GPU.
• Publish and open source cutting-edge AI research.
• Work on one of the fastest AI supercomputers in the world.
• Job stability with startup vitality.
• Simple, non-corporate work culture that respects individual beliefs.

About the company

Cerebras Systems builds the world's largest AI chip. The company works with leading model labs, global enterprises, and cutting-edge AI-native startups.