Senior AI Workload Orchestration Engineer

re-zoo-me; Singapore; Hybrid; SGD 180,000 - 240,000; Full time

Job summary

CoreWeave seeks a Senior Software Engineer to lead the AI Workload Orchestration Platform, shaping architecture for admitting, scheduling, and governing AI workloads across large GPU clusters using Kubernetes-native tooling.

You will collaborate with infrastructure, CKS, and managed inference teams, own platform reliability, observability, and scalability, and mentor engineers to advance CoreWeave's cloud AI capabilities.

Qualifications

• 8+ years of professional software engineering experience in distributed systems or cloud platforms.
• Strong proficiency in Go and design of large-scale production systems.
• Deep knowledge of Kubernetes internals, scheduling mechanisms, and controller-based architectures.
• Demonstrated experience designing or evolving orchestration, scheduling, or resource-management platforms.
• Proven ability to lead technical initiatives across teams without direct authority; strong operational mindset.

Responsibilities

• Own the technical vision and architecture for major portions of the AI Workload Orchestration Platform.
• Design scalable, reliable orchestration primitives for AI workloads across multiple schedulers and runtimes.
• Lead cross-team architecture reviews and drive alignment across infrastructure, CKS, and managed inference teams.
• Define platform standards for reliability, observability, capacity management, and operational excellence.
• Identify and resolve systemic performance, scalability, and fairness issues across large GPU clusters.
• Mentor senior engineers and grow technical leadership within the organization.
• Represent the platform in technical reviews and influence broader CoreWeave platform strategy.

Skills

Go

Kubernetes internals

Distributed systems

Production systems

AI workloads

Tools

Kueue

Volcano

Ray

SUNK (Slurm on Kubernetes)

Job description

CoreWeave seeks a Senior Software Engineer to lead the AI Workload Orchestration Platform, shaping architecture for admitting, scheduling, and governing AI workloads across large GPU clusters using Kubernetes-native tooling.

You will collaborate with infrastructure, CKS, and managed inference teams, own platform reliability, observability, and scalability, and mentor engineers to advance CoreWeave's cloud AI capabilities.