Staff Software Engineer

COREWEAVE SINGAPORE PTE. LTD.; Singapore; On-site; SGD 160,000 - 230,000; Full time

Benefits offered by this job

Discretionary bonus

Equity awards

Benefits package

Job summary

CoreWeave Singapore is seeking a Senior Software Engineer to lead the AI Workload Orchestration Platform, defining architecture for admitting, scheduling, and governing AI tasks across large GPU clusters using frameworks like Kueue, Volcano, and Ray.

You will own the technical vision for orchestration primitives, mentor engineers, and drive reliability, scalability, and developer experience as CoreWeave expands its cloud infrastructure.

Qualifications

• 5+ years of professional software engineering experience in distributed systems or cloud platforms.
• Strong proficiency in Go and production systems design.
• Deep knowledge of Kubernetes internals, scheduling, and controller-based architectures.
• Experience designing or evolving orchestration, scheduling, or resource-management platforms.
• Proven ability to lead technical initiatives across teams without direct authority.
• Strong operational mindset with experience owning mission-critical systems at scale.

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

Distributed systems

Leadership without authority

Cross-team influence

Platform scalability

Operational mindset

Tools

Go

Kubernetes

Kueue

Volcano

Ray

Job description

What You’ll Do:

As a Senior Software Engineer on the AI Workload Orchestration Platform team, you will act as a technical leader for CoreWeave's Kubernetes-native orchestration strategy for AI workloads.

You will define and evolve the architecture for how AI workloads are admitted, scheduled, and governed across large GPU clusters using frameworks such as Kueue, Volcano, and Ray . This platform serves as a strategic complement to SUNK (Slurm on Kubernetes) and underpins both training and inference workloads across the CoreWeave cloud.

This role requires strong systems thinking, cross-team influence, and a long-term view of platform scalability, reliability, and developer experience.

About the role:

• 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

Who You Are:

• 5+ years of professional software engineering experience, with deep expertise in distributed systems or cloud platforms
• Strong proficiency in Go and experience designing large-scale, long-lived 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 with experience owning mission-critical systems at scale

Preferred qualifications:

• Hands-on experience with Kueue, Volcano, Ray , or similar Kubernetes-native orchestration frameworks
• Background in AI infrastructure, ML platforms, HPC, or large-scale batch and streaming systems
• Deep understanding of scheduling concepts including fairness, pre-emption, quota management, and multi-tenant isolation
• Experience defining and operating SLOs , capacity models, and large-scale reliability improvements
• Contributions to open-source infrastructure or orchestration projects

Wondering if you're a good fit? We believe in investing in our people and value candidates who can bring their diverse experiences to our teams - even if you aren't a 100% skill or experience match.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast! We're in an exciting stage of hyper-growth that you will not want to miss out on. We're not afraid of a little chaos, and we're constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get set for takeoff, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!

The starting salary will be determined by job-related knowledge, skills, experience, and the market location. We strive for both market alignment and internal equity when determining compensation.

• In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).