Knowledge Architect

CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at www.coreweave.com. What you'll do The Knowledge Architecture team at CoreWeave owns how the Product and Engineering organization captures, structures, and shares everything it knows. We build the internal documentation, onboarding content, and technical education programs that let engineers find answers and get productive fast, and we set the standards and create the ontology infrastructure that keeps that knowledge accurate as the company scales. If you want your work used by every team in a company operating at the frontier of AI infrastructure, this is the team to join. About the role 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. In this role, you will: • 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. Who you are • 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 in using AI tools to scale and improve your 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. Preferred • Experience documenting cloud, Kubernetes, GPU, and AI and ML 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 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 troubleshooting. • Familiarity 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 reported. • Experience 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 product. 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 match. Here are a few qualities we've found compatible with our team. If some of this describes you, we'd love to talk. • You love turning an undocumented system into a page someone can actually follow. • You're curious about how things work, and you ask the question the engineer assumed everyone already knew the answer to. • You're an expert at structuring information so people find it without being told where it lives. • You like working with a small, collaborative, tight-knit team. • You'd rather fix the root cause of a recurring question than answer it again. Why CoreWeave? At CoreWeave, we work hard, have fun, and move fast! We're in an exciting stage of hyper-growth that you will not want to miss out on. We're not afraid of a little chaos, and we're constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: • Be Curious at Your Core • Act Like an Owner • Empower Employees • Deliver Best-in-Class Client Experien