Senior Content Engineer, KnowledgeOps

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 KnowledgeOps 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 patternsBuild and run docs-as-code pipelines: Git authoring, CI/CD builds, linting, link and code-sample validation, and publishingMake 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 accuracyAutomate 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 mattersEncode standards (user stories, release readiness, onboarding, security guidance) into templates, validators, and guided workflows rather than static documentsCapture tribal knowledge from engineering, product, and operations, and turn it into playbooks, decision guides, and self-service pathsMeasure 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 retirePartner with Engineering, Product, Security, Developer Relations, and Partner Programs so every release ships documented, discoverable, and supportableWhat we need to see:Bachelor's degree or equivalent experience, plus 8+ years in technical writing, developer documentation, or developer experience for complex software platformsHands-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 trustedInformation architecture skills: content modeling, taxonomy, and metadata for both navigation and machine retrievalEnough 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 implementationWays to stand out from the crowd:Experience building RAG pipelines, AI assistants, MCP servers, or agent skill and context libraries backed by documentationDocumentation 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 monitoringMeasurable reductions in support load or onboarding time through self-service knowledge systemsOpen source contributions or published work on docs-as-code, AI-assisted documentation, or knowledge engineeringYour 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 (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.SummaryLocation: US, Remote; US, TX, Remote; US, NY, Remote; US, OR, Remote; US, MA, Remote; US, WA, SeattleType: Full time