Knowledge Architect

Join our team as a Knowledge Architect, where you will play a crucial role in enhancing our documentation and knowledge infrastructure. You will be responsible for writing and maintaining internal technical documentation, building onboarding content, and capturing knowledge from engineers and subject matter experts. You will also maintain knowledge assets in Confluence and support the AI Developer Tools Hub. This is an exciting opportunity for someone with a passion for documentation and a desire to make a meaningful impact in a collaborative team environment.

Here are a few qualities we've found compatible with our team. If some of this describes you, we'd love to talk:

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.
• Experience auditing an existing documentation estate and remediating gaps in accuracy, coverage, or discoverability
• Demonstrated experience applying a documentation style guide and template set consistently, and in using AI tools to scale and improve your output
• Demonstrated experience interviewing engineers or subject matter experts and converting what you learn into published documentation
• Experience writing and maintaining technical documentation for a technical audience, such as systems documentation, runbooks, workflows, or developer guides

Requirements

• 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
• Experience owning content in Confluence or a comparable platform, including page structure, navigation, labeling, and templates

Experience with docs-as-code workflows

• 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
• 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 defining information architecture for a large or fragmented content estate
• Experience 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 match
• You like working with a small, collaborative, tight-knit team
• 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 love turning an undocumented system into a page someone can actually follow

Preferred

• Experience with enterprise search and content discoverability, including how structure and metadata affect retrieval
• Experience documenting cloud, Kubernetes, GPU, and AI and ML infrastructure
• You'd rather fix the root cause of a recurring question than answer it again

Pay

USD 134,000 - 179,000