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CoreWeave

Rents GPU cloud computing for AI developers

Knowledge Architect

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, or developer guides.
  • Demonstrated experience interviewing engineers or subject matter experts and converting what you learn into published documentation.
  • Experience owning content in Confluence or a comparable platform, including page structure, navigation, labeling, and templates.
  • Demonstrated experience applying a documentation style guide and template set consistently, and using AI tools to scale and improve documentation output.
  • Experience auditing an existing documentation estate 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.
  • Demonstrated ability to prioritize and deliver across multiple concurrent stakeholder teams.

Responsibilities

  • Write, edit, and maintain internal technical documentation for Product and Engineering teams, including systems documentation, workflows, runbooks, and guides.
  • Build and maintain onboarding and informational content for department and team spaces, and backfill coverage for teams not yet served.
  • Partner with engineering teams and subject matter experts to capture knowledge that is currently undocumented or held informally.
  • Maintain knowledge assets in Confluence, including space structure, navigation, labeling, and content lifecycle.
  • Support the AI Developer Tools Hub and other Knowledge Architecture-maintained hubs.
  • Take documentation requests through intake, scoping, delivery, and publication, and communicate scope, timelines, and status to requesting teams.
  • Run recurring audits against the published documentation estate for accuracy, coverage, and discoverability, and remediate identified gaps.

Desired Qualifications

  • Experience documenting cloud, Kubernetes, GPU, and AI and machine learning infrastructure.
  • Experience building or maintaining onboarding content for engineering organizations.
  • Experience with docs-as-code workflows.
  • Experience with enterprise search and content discoverability, including how structure and metadata affect retrieval.
  • Experience defining information architecture for a large or fragmented content estate.
  • Experience documenting high-performance computing or machine learning workload schedulers such as Slurm, Slurm on Kubernetes (SUNK), or Kueue, including day-2 operations such as upgrades, node drain states, and control plane troubleshooting.
  • Familiarity with the inference and training stack that machine learning platform teams build on, such as vLLM, SGLang, TensorRT-LLM, or NCCL, and with how benchmarks such as MLPerf are run and reported.
  • Experience writing for both platform engineers who operate a system and researchers or customers who consume it, such as runbooks and user-facing documentation for the same product.

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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