Knowledge Architect

Coreweave; Livingston; Hybrid; GBP 60,000 - 90,000; Full time

Job summary

Coreweave seeks an IC3 Knowledge Architect to write and maintain internal technical documentation for Product and Engineering teams. You will build onboarding content and manage the knowledge base in Confluence, collaborating with engineers and subject matter experts to capture and organize key information.

You will own the documentation lifecycle from scoping to publication, run audits for accuracy and coverage, and help improve discoverability across departments using docs-as-code workflows

Qualifications

• Experience auditing an existing documentation estate and remediating gaps in accuracy, coverage, or discoverability.
• Ability to apply a documentation style guide and templates consistently.
• Experience interviewing engineers or subject matter experts to capture tacit knowledge.
• Experience writing and maintaining technical documentation for a technical audience (systems docs, runbooks, guides).

Responsibilities

• Write, edit, and maintain internal technical documentation for Product and Engineering teams.
• Build onboarding content for engineering teams and backfill coverage.
• Maintain Confluence space structure, navigation, labeling, and content lifecycle.
• Take documentation requests through intake, scoping, delivery, and publication.
• Collaborate with engineers to capture undocumented knowledge and improve findability.
• Run recurring audits against KA estate for accuracy and discoverability.

Skills

Documentation

Confluence

Jira

CMS maintenance

Docs-as-code

Engineer interviews

Tools

Confluence

Jira

Job description

• As an IC3 (Practitioner) Knowledge Architect, you will add dedicated documentation and knowledge infrastructure capacity to our team
• You will write and maintain internal technical documentation for Product and Engineering teams, including systems documentation, workflows, runbooks, and guides, and you will build and maintain the onboarding content new engineers rely on in their first weeks
• You will work directly with engineers and subject matter experts to capture knowledge that today exists only in people’s heads, and you will help maintain the CMS structure, navigation, and content lifecycle that makes it findable
• You will work to the standards set by the Staff Knowledge Architect and take requests through our intake process from scoping to publication
• 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 KA-maintained hubs
• Take documentation requests through intake, scoping, delivery, and publication, and communicate scope, timelines, and status to requesting teams
• Run recurring audits against KA’s published estate for accuracy, coverage, and discoverability, and remediate the gaps you find

Experience auditing an existing documentation estate and remediating gaps in accuracy, coverage, or discoverabilityDemonstrated experience applying a documentation style guide and template set consistently, and in using AI tools to scale and improve your outputDemonstrated experience interviewing engineers or subject matter experts and converting what you learn into published documentationExperience writing and maintaining technical documentation for a technical audience, such as systems documentation, runbooks, workflows, or developer guidesExperience managing a request queue in Jira or a comparable system, including scoping work and committing to delivery datesDemonstrated ability to prioritize and deliver across multiple concurrent stakeholder teamsExperience owning content in Confluence or a comparable platform, including page structure, navigation, labeling, and templatesExperience with enterprise search and content discoverability, including how structure and metadata affect retrievalExperience with docs-as-code workflowsExperience writing for both the platform engineers who operate a system and the researchers or customers who consume it; for example runbooks and user‑facing documentation for the same productExperience documenting HPC or ML workload schedulers such as Slurm, Slurm on Kubernetes (SUNK), or Kueue, including day‑2 operations such as upgrades, node drain states, and control plane troubleshootingFamiliarity with the inference and training stack that ML platform teams build on, such as vLLM, SGLang, TensorRT-LLM, or NCCL, and with how benchmarks such as MLPerf are run and reportedExperience defining information architecture for a large or fragmented content estateExperience documenting cloud, Kubernetes, GPU, and AI and ML infrastructureExperience building or maintaining onboarding content for engineering organizations

Wondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams, even if you aren’t a 100% skill or experience matchYou like working with a small, collaborative, tight-knit teamYou’re curious about how things work, and you ask the question the engineer assumed everyone already knew the answer toYou’re an expert at structuring information so people find it without being told where it livesYou love turning an undocumented system into a page someone can actually followYou’d rather fix the root cause of a recurring question than answer it againHere are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk: