Director of AI Compute Services

CoreWeave is the AI Hyperscaler™, delivering a cloud platform of cutting edge services powering the next wave of AI. Our technology provides enterprises and leading AI labs with the most performant, efficient and resilient solutions for accelerated computing. Since 2017, CoreWeave has operated a growing footprint of data centers covering every region of the US and across Europe. CoreWeave was ranked as one of the TIME100 most influential companies of 2024.

As the leader in the industry, we thrive in an environment where adaptability and resilience are key. Our culture offers career-defining opportunities for those who excel amid change and challenge. If you’re someone who thrives in a dynamic environment, enjoys solving complex problems, and is eager to make a significant impact, CoreWeave is the place for you. Join us, and be part of a team solving some of the most exciting challenges in the industry.  

CoreWeave powers the creation and delivery of the intelligence that drives innovation. 

Position Overview

CoreWeave is seeking an experienced and innovative Director of AI Compute Services. In this role you will focus on architecting CoreWeave's compute services like Coreweave Kubernetes Service - powering the AI revolution. You will build and lead a world-class team, tackling the complex challenges of designing, building, and operating world-class compute services for the most demanding AI workloads on the planet. You will be focusing on achieving the highest levels of service quality, scalability and performance. This leadership position requires a strong combination of technical expertise, strategic vision, and business acumen. You will work closely with yours in Engineering, Product and Sales to shape the compute infrastructure roadmap, drive innovation, and ensure the reliability, security, and scalability of the CoreWeave Cloud Platform.

 

Key Responsibilities

Strategic Leadership

• Define and execute CoreWeave’s AI compute roadmap in alignment with our growth trajectory and customer needs.
• Collaborate with product, infrastructure, sales, and engineering teams to support GPU-intensive workloads and strategic client deployments.
• Grow and lead a high-performance team of infrastructure, systems, and AI platform engineers.

Infrastructure & Optimization

• Design and manage large-scale GPU cluster environments.
• Help drive architecture decisions around high-throughput networking, low-latency storage, and resource scheduling for AI/ML workloads.
• Ensure optimal performance and utilization across massive-scale GPU deployments.

Innovation & Technical Execution

• Evaluate and integrate next-gen hardware and software technologies.
• Develop scheduling, orchestration, and containerization strategies (e.g., Kubernetes, Slurm) tailored for deep learning workloads.
• Provide internal and external clients with robust, secure, and performant AI environments.

Operational Excellence

• Define customer-centric SLAs and Implement effective monitoring systems to ensure infrastructure uptime and efficiency.
• Optimize for both performance and cost-efficiency across GPU-based compute resources.

Client & Partner Collaboration

• Support strategic client engagements with technical solutions and infrastructure design.
• Represent CoreWeave in partner/vendor relationships with hardware and software ecosystem players.
• Act as a technical voice of the customer in shaping internal product and infrastructure roadmaps.
• Collaborate effectively with open source communities

Qualifications

• 10+ years of experience in infrastructure, high-performance compute, or cloud systems
• 5+ years of experience in engineering leadership roles
• Proven track record of building and scaling high-performing engineering teams and fostering a positive and productive team culture.
• Experience building and developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware architecture
• Good understanding of AI/ML model training, inference workflows, and performance tuning
• Bachelor’s or Master's degree in Computer Science or Compute Architecture, or equivalent practical experience.

Preferred Experience

• Experience at a cloud provider or hyperscaler.
• Familiarity with MLOps, workload telemetry, and multi-tenant compute environments.
• Demonstrated success scaling infrastructure for LLMs or foundation models.
• Strong bu