N

NVIDIA

Designs the chips and software that power AI

Documentation Technical Program Manager

Program ManagementPosted on Nov 10
Full-timeIn-person

About the Job

Requirements

  • At least 8 years of relevant experience.
  • A bachelor's degree in a technical or related field, or equivalent experience.
  • A strong commitment to technical documentation, demonstrated through hands-on improvements to clarity, consistency, and usability informed by developer feedback and quality signals.
  • Experience organizing developer documentation, defining journeys for different customer types and segments, and designing effective navigation.
  • Strong program management skills, including planning, prioritization, dependency management, risk escalation, and driving complex programs across multiple teams.
  • Familiarity with documentation workflows from content development and review through release and maintenance, including Git/GitLab collaboration, build and publication processes, and continuous integration and continuous delivery concepts.
  • Experience with automotive, embedded software, or similarly complex platform products.
  • Ability to communicate clearly in writing and verbally, exercise sound judgment, and align technical writers, engineering, product, quality assurance, and customer-facing teams.

Responsibilities

  • Own the DriveOS documentation strategy and information architecture; establish shared content standards, terminology, and organization across teams and product variants; and drive closure of gaps, duplication, and inconsistencies.
  • Define documentation journeys for specific customer types and segments, and create navigation maps connecting guides, API references, release notes, and migration information to help developers find appropriate content from initial evaluation through development and deployment.
  • Plan and drive documentation delivery across DriveOS releases and product variants, aligning scope, owners, milestones, dependencies, customer commitments, and delivery paths.
  • Lead cross-functional execution with writers, engineers, and reviewers; track status; resolve blockers; and manage documentation reviews, approvals, defect closure, and release exceptions.
  • Coordinate publication and release communications, ensuring approved documentation is correctly versioned, mapped to supported variants, and available through appropriate internal and external channels; follow through on late deliverables.
  • Gather feedback from developers and customer-facing teams, assess how easily users find information and complete key tasks, and prioritize documentation improvements with content owners.
  • Improve dashboards, issue tracking, handoff guides, and automation by defining data and workflow requirements with the teams that own the tools.
  • Use artificial intelligence and large language models to propose documentation journeys and navigation maps, identify content gaps and inconsistencies, and support consistent terminology and structure; validate proposed changes with technical writers and subject matter experts before publication.

Desired Qualifications

  • Experience coordinating automotive safety and cybersecurity deliverables and their review processes, including ISO 26262 or ISO 21434 contexts.
  • Familiarity with API/ABI documentation, functional or performance test reports, and third-party license reporting.
  • Practical experience using artificial intelligence or large language models to map documentation journeys, identify gaps and inconsistencies across documents, or improve content organization, with a clear approach to validating results; experience with scripting, workflow automation, dashboards, or data validation is also valuable.
  • Experience with GitLab, Sphinx, reStructuredText, Doxygen, DITA, or related technical documentation toolchains.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

Recently Posted Jobs

Explore more opportunities at NVIDIA

See more jobs