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CoreWeave

Rents GPU cloud computing for AI developers

Senior Technical Program Manager - Fleet Delivery & Capacity Management

Program ManagementUpdated on Nov 13
Full-timeIn-person

About the Job

Requirements

  • A bachelor's degree in Computer Engineering, Computer Science, or a related technical field, or equivalent practical experience.
  • At least 7 years of experience in technical program management or related engineering delivery roles, with demonstrated success leading complex compute infrastructure deployment programs.
  • Technical understanding of server provisioning, networking dependencies, hardware/software integration, validation, and operational readiness in large-scale infrastructure environments.
  • Experience translating business and customer requirements into technical delivery plans with clear scope, dependencies, milestones, and acceptance criteria.
  • Ability to lead cross-functional execution, influence without direct authority, and drive prioritization and tradeoff decisions with engineering, operations, and business stakeholders.
  • Ability to independently investigate delivery data, reconcile conflicting sources, define meaningful metrics, and guide dashboard development to support planning and execution.
  • Experience establishing effective delivery processes in rapidly changing environments with incomplete data and evolving requirements.
  • Strong written and verbal communication skills, including the ability to explain delivery feasibility, risks, and tradeoffs to technical teams and business leaders.

Responsibilities

  • Lead Fleet delivery programs from infrastructure handover through provisioning, validation, and operational acceptance, tracking upstream readiness dependencies before handover.
  • Partner with Product, Go-to-Market, and Capacity Planning to translate customer requirements—including instance type, location, quantity, configuration, and required dates—into actionable Fleet delivery plans.
  • Maintain an integrated view of delivery commitments, forecasts, dependencies, blockers, and accountable owners across engineering and operations teams.
  • Assess gaps between business demand and Fleet delivery capabilities, develop mitigation options, and drive prioritization and resource tradeoff decisions with the appropriate leaders.
  • Represent Fleet in cross-functional delivery forums, ensure the right technical owners participate, and carry decisions and action items through to completion.
  • Drive resolution of provisioning and validation blockers, escalate based on delivery impact, and promptly communicate forecast-date changes.
  • Establish provisioning, validation, and operational acceptance criteria with engineering and operations owners, including documentation and explicit ownership of accepted exceptions.
  • Define and use metrics for delivery throughput, time from handover to readiness, forecast accuracy, and capacity blocked by cause and age; reconcile discrepancies affecting delivery decisions.
  • Identify recurring bottlenecks and translate deployment lessons and upcoming requirements into prioritized improvements to Fleet tooling, automation, and processes.

Desired Qualifications

  • Experience coordinating infrastructure deployment readiness for new GPU platforms or compute service offerings.
  • Familiarity with data center infrastructure dependencies, including power, cooling, and networking, and their impact on compute deployment.
  • Experience partnering with Product, Go-to-Market, and Capacity Planning teams to align infrastructure delivery with customer requirements and business priorities.
  • Experience defining provisioning, validation, and operational acceptance criteria, including documentation and ownership of outstanding issues.
  • Experience coordinating reprovisioning, hardware refreshes, or infrastructure transitions that support existing customers.
  • Experience using analytical tools or query languages, such as SQL, to investigate infrastructure data and improve delivery reporting.
  • Demonstrated success improving provisioning throughput, delivery predictability, or time to operational readiness through tooling, automation, or process changes.

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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