Job opportunity
Staff Distributed Systems Engineer
Cerebras
Lead distributed systems engineering at Cerebras Systems, building Kubernetes-based inference infrastructure for globally distributed AI workloads.
As a Staff Engineer on the Inference Platform team, you will own orchestration connecting cloud components with machine learning services. You will design production software, guide architecture, and address unsolved platform challenges. The work spans Kubernetes custom resource definitions, security policies, CI/CD, observability, networking, and reliability. Cerebras builds AI hardware designed for high-speed training and inference.
Key Responsibilities:
Design, develop, test, and maintain production software
Shape platform architecture, service boundaries, and technical roadmaps
Architect active-active systems with failover and graceful degradation
Lead production incidents, capacity planning, and post-incident improvements
Influence engineering decisions through reviews, pairing, and standards
Requirements:
Eight or more years of software engineering experience
Experience operating large-scale distributed systems or cloud infrastructure
Deep distributed systems expertise, ideally with Kubernetes
Proficiency in Go or C++ production development
Experience with TLS, mTLS, observability, and SLO-driven operations
Bring distributed systems judgment, Kubernetes expertise, and production engineering skills to Cerebras Systems’ Inference Platform team.
#J-18808-Ljbffr
Apply on source site As a Staff Engineer on the Inference Platform team, you will own orchestration connecting cloud components with machine learning services. You will design production software, guide architecture, and address unsolved platform challenges. The work spans Kubernetes custom resource definitions, security policies, CI/CD, observability, networking, and reliability. Cerebras builds AI hardware designed for high-speed training and inference.
Key Responsibilities:
Design, develop, test, and maintain production software
Shape platform architecture, service boundaries, and technical roadmaps
Architect active-active systems with failover and graceful degradation
Lead production incidents, capacity planning, and post-incident improvements
Influence engineering decisions through reviews, pairing, and standards
Requirements:
Eight or more years of software engineering experience
Experience operating large-scale distributed systems or cloud infrastructure
Deep distributed systems expertise, ideally with Kubernetes
Proficiency in Go or C++ production development
Experience with TLS, mTLS, observability, and SLO-driven operations
Bring distributed systems judgment, Kubernetes expertise, and production engineering skills to Cerebras Systems’ Inference Platform team.
#J-18808-Ljbffr