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Senior Content Engineer, Ops
Job in
Seattle, King County, Washington, 98101, USA
Listed on 2026-10-21
Listing for:
Nvidia
Full Time
position Listed on 2026-10-21
Job specializations:
-
Software Development
AI Engineer (Applied/Software)
Job Description & How to Apply Below
Build the systems that deliver Simulation Technology knowledge to developers, partners, internal teams, and the AI agents that increasingly sit between them and our documentation. Our Knowledge Ops team sets the information architecture and quality standards for Omniverse, Isaac Sim, and OpenUSD documentation. You'll build the automation, pipelines, and AI-ready infrastructure that apply those standards at scale, and work with documentation leads to refine the architecture based on what you learn.
You're a writer who builds: as comfortable in Git, CI, or Python as in a style guide, and fluent with LLMs in daily work. We build systems where the right way is easier than the wrong way. For you, that means turning documentation, standards, and tribal knowledge into tooling, templates, and self-service paths, so fewer people have to ask "how do I…?"What
you'll be doing:
Collaborate with documentation leads on knowledge architecture, sharing implementation feedback (what works, breaks, and scales) to refine content models, information architecture, and AI-readiness patterns
Build and run docs-as-code pipelines:
Git authoring, CI/CD builds, linting, link and code-sample validation, and publishing
Make knowledge AI-ready: structure and package content for RAG, internal assistants, and agentic workflows, including llms.txt, MCP-accessible sources, agent skills and context kits, and evaluation sets for answer accuracy
Automate the content lifecycle with LLMs and scripting, from drafting and updating to auditing, with checks for freshness, code accuracy, and terminology drift, and human review where judgment matters
Encode standards (user stories, release readiness, onboarding, security guidance) into templates, validators, and guided workflows rather than static documents
Capture tribal knowledge from engineering, product, and operations, and turn it into playbooks, decision guides, and self-service paths
Measure outcomes such as time-to-first-success, support deflection, repeat questions, and AI answer quality, and use the data to decide what to build, fix, or retire
Partner with Engineering, Product, Security, Developer Relations, and Partner Programs so every release ships documented, discoverable, and supportable
What we need to see:
Bachelor's degree or equivalent experience, plus 8+ years in technical writing, developer documentation, or developer experience for complex software platforms
Hands-on docs-as-code experience:
Git, pull request review, Markdown/RST, static site generators (Sphinx, MkDocs, Docusaurus, or similar), and CI/CDWorking proficiency in Python or similar to automate content tasks, transform data, and integrate with APIsPractical experience applying LLMs to content workflows (prompting, retrieval and grounding, output evaluation) and sound judgment about where AI can be trusted
Information architecture skills: content modeling, taxonomy, and metadata for both navigation and machine retrieval
Enough technical depth to read code and APIs, verify accuracy, and write working examplesA systems mindset: you fix the class of problem, not just the instanceA collaborative style: you turn design intent into working systems and give leads clear, constructive feedback grounded in implementation
Ways to stand out from the crowd:
Experience building RAG pipelines, AI assistants, MCP servers, or agent skill and context libraries backed by documentation
Documentation experience in graphics, simulation, robotics, or real-time systems; familiarity with USD, Omniverse, Isaac Sim, or ROSContent quality automation you've built, such as Vale or custom linters, doc test harnesses, or freshness monitoring
Measurable reductions in support load or onboarding time through self-service knowledge systems
Open source contributions or published work on docs-as-code, AI-assisted documentation, or knowledge engineering
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 144,000 USD - 230,000 USD for Level 4, and 176,000 USD - 276,000 USD for Level 5.You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until October 20, 2026.This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate…
Position Requirements
10+ Years
work experience
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