Staff Product Manager - Core Compute Services

Highlights

• Lead roadmap for core compute powering all AI workloads on CoreWeave.
• Shape next-gen compute for training, inference, agents and sandboxes.
• Own instance lifecycle, health, isolation and capacity reservation semantics.

What they offer

• Tuition Reimbursement
• Ability to Participate in Employee Stock Purchase Program (ESPP)
• Mental Wellness Benefits through Spring Health
• Family-Forming support provided by Carrot
• Paid Parental Leave
• Flexible, full-service childcare support with Kinside
• 401(k) with a generous employer match
• Flexible PTO
• Catered lunch each day in our office and data center locations
• A casual work environment
• A work culture focused on innovative disruption

Ideal candidate

A strategic yet deeply technical product leader who loves foundational infrastructure and thrives partnering with engineers and customers to turn complex compute challenges into reliable, scalable platforms for AI innovation.

Requirements

• 8+ years of professional experience, with 5+ years in Product Management of cloud services or in the AI/ML market segment
• Deep understanding of cloud compute at the instance layer: how compute is provisioned, delivered, kept current, isolated, and reclaimed at scale
• Proven ability to lead cross functional teams, with strong decision-making, project management, and mentoring skills
• Demonstrated experience working closely with customers to identify needs and translate them into product features and solutions
• Excellent verbal and written communication skills with the ability to influence cross-functional teams and stakeholders
• Ability to think strategically while being able to dive into technical details to guide engineering teams
• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field
• Hands on experience with a large-scale compute or instance service, such as EC2, Google Compute Engine, Azure Compute
• Familiarity with accelerated compute, high-performance interconnect, and the behavior of large multi-node workloads