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CoreWeave

Rents GPU cloud computing for AI developers

Knowledge Architect - Fleet

Technical Writing +1Updated on Nov 13
Full-timeIn-person

About the Job

Requirements

  • Experience writing and maintaining technical documentation for a technical audience, such as systems documentation, runbooks, workflows, escalation guides, or developer guides; experience with Fleet teams is a strong plus.
  • Demonstrated experience interviewing engineers or subject matter experts and converting what is learned into published documentation.
  • Experience building or maintaining onboarding programs or curricula for technical or operations teams.
  • Experience owning content in Confluence or a comparable platform, including page structure, navigation, labeling, and templates, and applying a documentation style guide and template set consistently.
  • Experience auditing an existing body of documentation and remediating gaps in accuracy, coverage, or discoverability.
  • Experience managing a request queue in Jira or a comparable system, including scoping work and committing to delivery dates.
  • Willingness to learn cooperation across multiple concurrent stakeholder teams, including teams that operate around the clock and across regions.

Responsibilities

  • Under the guidance of Knowledge Architecture management and FRO-OED, assist in building and maintaining the FROps onboarding curriculum, including role-based paths for operations engineers, quarterbacks, and operations managers, and extend coverage to FROps sub-teams and partner teams not yet served.
  • Work with Knowledge Architecture and FRO-OED to develop measurements for onboarding effectiveness for new operations engineers, including time to productivity and new-hire satisfaction, and iterate the curriculum based on findings.
  • Write, edit, and maintain internal technical documentation for FROps and Fleet Engineering teams, including systems documentation, workflows, runbooks, escalation guides, and reference material such as the FROps Vocabulary and Region Quirks.
  • Partner with FRO-OED to define and apply documentation standards for the FRO Confluence space, and align those standards with Knowledge Architecture's Product and Engineering-wide standards and templates.
  • Partner with operations engineers, Fleet Engineering teams, and external partner organizations to capture knowledge that is currently undocumented or held informally, including site bring-up patterns, incident learnings, and tooling workflows.
  • Maintain knowledge assets in the FRO and Fleet Confluence spaces, including space structure, navigation, labeling, templates, and content lifecycle, and consolidate duplicated or fragmented content.
  • Take documentation requests from FROps and Fleet Engineering through intake, scoping, delivery, and publication, and communicate scope, timelines, and status to requesting teams.
  • Run recurring audits of FROps published knowledge assets for accuracy, coverage, and discoverability, and remediate identified gaps, prioritizing content used during on-call, incident response, and new site stand-up.
  • Escalate work requiring staff-level strategy or standards decisions to the Staff Knowledge Architect, and surface FROps prioritization questions to FRO-OED leadership.

Desired Qualifications

  • Experience documenting data center operations, bare metal provisioning, hardware lifecycle, or GPU and AI infrastructure.
  • Experience working with or documenting for operations, site reliability engineering, or on-call teams, including runbooks used during incident response.
  • Familiarity with Kubernetes, Redfish, AWX or Ansible, Grafana, and PagerDuty, or demonstrated ability to learn operational tooling quickly.
  • Experience with documentation-as-code workflows, including Git, Markdown, and pull request review.
  • Experience with enterprise search and content discoverability, for example Glean, including how structure and metadata affect retrieval.
  • Experience defining information architecture for a large or fragmented body of content.

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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