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CoreWeave

Rents GPU cloud computing for AI developers

Senior Manager - Production Engineering

Engineering LeadershipUpdated on Nov 13
Full-timeIn-person

About the Job

Requirements

  • A bachelor's degree in Computer Science, Engineering, or a related field is required.
  • At least 10 years of experience in a leadership or senior management role at a cloud provider, hyperscaler, or high-growth technology company is required.
  • Experience hiring, developing, and managing geographically distributed, 24x7 engineering teams is required.
  • Experience designing and implementing incident management processes, including on-call rotations, escalation paths, postmortems, and service-level objective and service-level agreement frameworks, is required.
  • A solid foundation in systems engineering and deep understanding of distributed systems, networking, and storage architecture are required.
  • Strong cross-functional collaboration skills and the ability to influence product, platform, hardware, and security teams are required.

Responsibilities

  • Contribute to and execute the site reliability engineering vision, strategy, and roadmap for large-scale distributed cloud infrastructure.
  • Lead and mentor a high-performing site reliability engineering team, promoting ownership, collaboration, and continuous learning.
  • Champion automation-first practices using artificial intelligence, Terraform, Kubernetes, and infrastructure as code to reduce toil and manual interventions.
  • Establish and evolve operational excellence practices that make the platform proactive and propagate organizational learning.
  • Drive incident management, postmortem culture, root cause analysis, and system-hardening initiatives.
  • Collaborate with engineering, product, and customer support teams to build scalable, resilient, and self-healing systems.
  • Evolve the on-call strategy and processes to support a globally distributed 24x7 platform with minimal disruptions.

Desired Qualifications

  • Experience building platform tooling and internal developer portals to improve engineering velocity and operational visibility.
  • Familiarity with GPU-accelerated workloads, including resource isolation, scheduling, and performance tuning.
  • Experience working in AI infrastructure environments supporting training or inference at scale.
  • A background in compliance, reliability risk modeling, or operational maturity assessments, such as recovery time and recovery point objectives or chaos engineering.
  • Prior leadership experience in bare-metal infrastructure environments, such as custom data centers, edge computing, or high-performance computing clusters.
  • Working knowledge of data processing units, service mesh architectures, and multi-tenant security models.

About the Company

CoreWeave

Rents GPU cloud computing for AI developers

CoreWeave rents cloud computing to AI labs and businesses that train models and run them in production for research and commercial applications. Its platform combines NVIDIA graphics chips, storage, networking, and software built for demanding AI workloads across connected clusters scaled to fit each project. CoreWeave Forge connects tools for tracking experiments, testing models, and improving AI systems using feedback from production. Customers rent computing capacity through committed contracts or usage charges, while managed services handle the infrastructure needed to keep large workloads running. CoreWeave was founded in 2017 and is headquartered in Livingston, New Jersey.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Livingston, NJ
Founded
2017

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