Senior Software Engineer - AI Workload Orchestration

Coreweave; United States; On-site; USD 182,000 - 242,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

Life Insurance

ESPP

401(k) match

Paid parental leave

Flexible PTO

Catered lunch

Job summary

CoreWeave is seeking a Senior Software Engineer II (IC4) to join the AI Workload Orchestration Platform team in the US. You will help build and operate the Kubernetes-native platform for admitting, scheduling, and operating AI workloads at scale.

The role involves owning platform components end-to-end, improving latency and utilization, and collaborating across teams to ensure clean interfaces. Mentoring engineers and contributing to platform reliability are key parts of the role.

Qualifications

• 5–8 years of professional software engineering in distributed systems or cloud platforms.
• Strong Go experience; Python or C++ a plus.
• Solid Kubernetes fundamentals: APIs, controllers, production services.

Responsibilities

• Design, build, and operate Kubernetes-native services for AI workload orchestration and scheduling.
• Own platform components end-to-end, including design, implementation, testing, and on-call support.
• Improve scheduling latency, cluster utilization, and workload reliability through metrics-driven engineering.
• Contribute to architectural discussions across services and influence design decisions within the platform.
• Work closely with adjacent teams (CKS, infrastructure, managed inference) to ensure clean interfaces and integrations.
• Mentor junior engineers and raise the quality bar for code, design, and operations.

Skills

Go

Kubernetes

Distributed systems

Scheduling concepts

Tools

Kueue

Volcano

Ray

Kubeflow

Argo Workflows

Job description

CoreWeave is seeking a Senior Software Engineer II (IC4) to join the AI Workload Orchestration Platform team in the US. You will help build and operate the Kubernetes-native platform for admitting, scheduling, and operating AI workloads at scale.

The role involves owning platform components end-to-end, improving latency and utilization, and collaborating across teams to ensure clean interfaces. Mentoring engineers and contributing to platform reliability are key parts of the role.