CPU CORE DOCUMENTATION ENGINEER

THE ROLE
As a CPU Core Documentation Engineer, you will have a unique opportunity to work with the entire design community — from CPU to SOC teams — to produce client's next-generation CPU internal and external documentation. This is a modern technical documentation role: you will apply AI tooling and agentic workflows to accelerate drafting, review, validation, and publication, while remaining the human authority accountable for technical accuracy and quality of everything that ships.

THE PERSON
You enjoy working as part of a team and have strong collaboration skills. You possess both strong verbal and written communication skills. You are an early adopter of AI tools and are energized — not threatened — by the opportunity to redesign how documentation gets produced. You enjoy automation to save time and effort, but also to provide flexibility and configurability. You exercise sound judgment about where AI accelerates work and where human expertise and verification are non-negotiable. You enjoy learning new skills that help you work more effectively and efficiently. Does this describe you? If so, then join us!

KEY RESPONSIBILITIES
End-to-end ownership for the delivery of the technical documentation for client's CPU Cores.
Create, edit, drive legal and technical reviews, and publish technical documentation (errata, data-books, white papers, application notes, Processor Programming Reference, and Web page content) via revision control or as specified by the document owners and process.
Apply large language models and AI-assisted authoring tools to draft, summarize, restructure, and copy-edit technical content — with rigorous human review, fact-checking, and validation against design source-of-truth before publication.
Build and maintain AI-enabled documentation workflows: prompt libraries, reusable prompt templates, retrieval over internal design collateral, and scripted or agentic pipelines that reduce manual effort in the doc toolchain.
Use AI to improve documentation quality at scale — consistency checking, terminology and style enforcement, cross-reference and errata validation, gap analysis, and localization readiness.
Proactively solicit feedback to ensure delivered documents meet customer requirements including accessibility, relevance, accuracy, clarity, consistency, and timeliness.
Partner with the CPU design team to create and maintain specific design files for input into the document delivery process, including structuring content so it is machine-readable and consumable by AI tooling.
Champion responsible AI use within the documentation function: adhere to client data-handling and confidentiality policies, understand model limitations and hallucination risk, and advocate best practices across the team.

PREFERRED EXPERIENCE
Hands-on experience using AI/LLM tools (e.g., ChatGPT, Claude, Copilot, or equivalent) in a professional technical writing or engineering workflow, including effective prompt engineering and critical evaluation of model output.
Demonstrated ability to integrate AI into day-to-day production work — not just experimentation — with a clear understanding of when to trust, verify, or reject generated content.
Proficiency with Microsoft Office and OpenOffice software.
Familiar with automating tasks with scripting languages such as Python, Perl, Ruby, etc.
Experience creating and using structured documentation (e.g., Extensible Markup Language, XML, and Open Document Text, ODT), and an appreciation for how structured content enables AI-assisted and automated publishing.
Understanding of and experience with Revision Control Systems (e.g., Perforce, CVS, Subversion, GIT, etc.).
Highly motivated to seek out solutions and willing to learn new skills — including rapidly evolving AI tooling — to fulfill job requirements.
Excellent writing skills in the English language; editing and organizational skills required.
Good understanding of engineering terminology used within the semiconductor industry.

ADDITIONAL EXPERIENCE DESIRED
Experience with retrieval-augmented generation (RAG), document chunking/indexing, or building AI agents and automations over an internal knowledge base.
Familiarity with docs-as-code practices and CI/CD-style publishing pipelines.
Familiarity or first-hand experience with CPU Design.
Experience with x86 or other CPU Instruction Set Architecture (ISA).
Understanding of IT Infrastructure such as servers, networking, storage, operating systems, etc.


ACADEMIC CREDENTIALS
BS, MS, or PhD degree in Electrical, Computer Engineering, or related field of study.


Notes:

This is a part-time role