Knowledge Architect, CoreWeave
$134-179k
Offers ESPP
The essential cloud for AI
Be an early applicant
The essential cloud for AI
1001+ employees
Be an early applicant
$134-179k
Offers ESPP
1001+ employees
Company mission
To manage the complexities of AI growth to make supercomputing accessible and push the limits of what's possible.
Role
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
- 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
Desirable
- 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
What the job involves
- 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
Our take
As AI continues to dominate the tech landscape, the demand for faster, more efficient cloud infrastructure is only intensifying. Traditional cloud providers often struggle with the sheer speed and scale required to power advanced AI models, leaving a gap for more specialized players. And that's where CoreWeave comes in, a company purpose-built to handle the heavy computational lift that the AI era demands.
CoreWeave's story is an interesting one too. What began in 2017 as a small crypto mining venture has evolved into one of the leading AI-focused cloud providers in the world. Its data centers are packed with high-end GPUs optimized for machine learning and generative AI, serving major clients like Microsoft and OpenAI. By designing its infrastructure around the needs of modern AI workloads rather than retrofitting older systems, CoreWeave has carved out a distinct and highly valuable niche in the market.
That focus in paying off in a big way too. Analyst project CoreWeave's revenue to soar from $5.3B in 2025 to the mid-$20Bs by 2028, up from just $16M in 2022. While there is competition from tech giants like Amazon and Google, CoreWeave's speed, specialization, and bold investment strategy put in in a very powerful position to keep riding (and helping shape) the AI boom.
Steph
Company Specialist at Welcome to the Jungle
Insights
194% employee growth in 12 months
Company
Funding (last 2 of 5 rounds)
May 2024
$1.1bn
SERIES C
May 2023
$200m
SERIES B
Total funding: $1.7bn
Company HQ
Civic Center, New York, NY
Leadership
Michael Intrator
(Co-Founder & CEO)Previously, Michael was a Principal Portfolio Manager at Natsource Asset Management for over 15 years. He also served as the CEO of Hudson Ridge Asset Management before co-founding CoreWeave in 2018.
Brian Venturo
(Co-Founder & CSO)Brian spent nearly 6 years at Natsource Asset Management as a Portfolio Manager before becoming a Partner at Hudson Ridge Asset Management. After co-founding CoreWeave he served as the CTO until 2024 when he moved into his current role of Chief Strategy Officer.
Brannin McBee
(Co-Founder & CDO)Brannin has a history in Proprietary Trading, having previously worked at Windy Bay Power and Active Power Investments. He also served as a VP at Fourth Floor Coastal and as an Associate at Elustria Capital PArtners.
Peter Salanki
(Co-Founder & CTO)Peter Previously served as a Director of Americas at Sandvine. Prior to that, he spent 11 years at Procera Networks as a Solutions Architect, Lead Architect, and Principal Solutions Architect.
Nitin Agrawal
(CFO)Nitin joined CoreWeave in 2024 as CFO. Prior to this, he was the VP of Finance at Google Cloud and CFO at Mapbox. He also spent nearly 5 years at AWS as CFO of Compute Services and 7 years at Microsoft as Group Manager of Finance.
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