AI Technical Writer

Hudson Manpower

$90K — $110K *
Consumer Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of technical writing experience in software or related technical fields.
  • 3+ years of experience in document control or content governance.
  • Proficient in transforming source code and runbooks into structured documentation.
  • Strong skills in information architecture including taxonomy and metadata management.
  • Ability to create technical manuals and specifications accurately.
  • Experience collaborating with technical teams including developers and engineers.
  • Hands-on experience with Markdown, Git, and Docs-as-Code workflows.

Responsibilities

  • Create comprehensive technical overviews, service documentation, and specifications.
  • Develop summaries to enhance AI knowledge retrieval efficiency.
  • Design documentation taxonomies, indexes, and structured content flows.
  • Organize content using appropriate metadata for various AI use cases.
  • Author prompts and instructions for AI agents and reusable skills.
  • Convert complex technical standards into version-controlled formats.
  • Conduct interviews with engineering teams to document implementation insights.

Benefits

  • Hybrid work environment with a base in Farmington Hills, MI.
  • Opportunities for collaborative work with technical teams.
  • Support for personal growth in AI-focused documentation skills.
Full Job Description
Job Summary

We are seeking an experienced AI Technical Writer to develop and govern structured knowledge used by production AI agents. This role focuses on transforming engineering documentation, source code, configurations, standards, and technical knowledge into concise, structured content that AI systems can accurately retrieve and use. The ideal candidate has strong technical writing, information architecture, documentation governance, and Docs-as-Code experience.

Key Responsibilities
  • Create service overviews, runbooks, technical specifications, schemas, standards, and glossary documentation.
  • Develop concise summaries that improve AI knowledge retrieval.
  • Design taxonomies, metadata, indexes, cross-links, and structured documentation.
  • Apply metadata to organize content by domain, system, and AI use cases.
  • Author AI prompts, reusable skills, agent instructions, and supporting documentation.
  • Convert engineering, security, governance, and platform standards into version-controlled documentation.
  • Interview engineering teams to capture technical decisions and implementation details.
  • Manage documentation through governance, security, compliance, and approval workflows.
  • Maintain naming conventions, controlled vocabularies, and glossary definitions.
  • Review, update, archive, and retire outdated documentation.
  • Work within Git-based documentation workflows using pull requests and validation processes.


Required Qualifications
  • 5+ years of technical writing experience in software, infrastructure, platform engineering, or related technical environments.
  • 3+ years of document control, content governance, or controlled documentation experience.
  • Experience creating documentation from source code, configurations, specifications, and engineering runbooks.
  • Strong information architecture skills including taxonomy, metadata, indexing, and cross-linking.
  • Experience writing technical manuals, standards, reference documentation, and technical specifications.
  • Strong terminology management and vocabulary governance skills.
  • Experience collaborating with developers, engineers, architects, and governance teams.
  • Hands-on experience with Markdown, Git, version control, and Docs-as-Code workflows.
  • Excellent technical writing skills with the ability to write concise, structured documentation.
  • Must be able to work in a hybrid environment in Farmington Hills, MI.

Preferred Qualifications
  • Experience writing AI prompts, agent instructions, reusable AI skills, or LLM documentation.
  • Understanding of AI retrieval systems, context windows, and context management.
  • Experience with YAML, JSON frontmatter, schemas, and structured content.
  • Familiarity with AI orchestration, retrieval systems, or Model Context Protocol (MCP).
  • Experience with Git workflows, pull requests, CI validation, and CLI-based documentation.
  • Knowledge of ontologies, knowledge graphs, semantic models, or controlled vocabularies.
  • Basic understanding of Python, TypeScript, Terraform, or YAML.
  • Experience in regulated industries such as Banking, Financial Services, or Cybersecurity.

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