Senior Content Engineer, KnowledgeOps

What you'll do

• Build and manage docs-as-code pipelines using Git, CI/CD, and Python for linting and publishing.
• Structure and package content for RAG, internal assistants, and agentic workflows to make knowledge AI-ready.
• Automate the content lifecycle using LLMs and scripting to audit for freshness, accuracy, and terminology drift.
• Encode standards into templates, validators, and guided workflows to replace static documentation.
• Convert tribal knowledge from engineering and product teams into playbooks and self-service paths.
• Measure and analyze outcomes like time-to-first-success and AI answer quality to prioritize system improvements.
• Refine content models and information architecture based on implementation feedback and scalability requirements.

What we're looking for

• Bachelor's degree or equivalent experience.
• 8+ years of experience in technical writing, developer documentation, or developer experience for complex software platforms.
• Hands-on experience with docs-as-code, including Git, pull request review, Markdown/RST, and static site generators.
• Working proficiency in Python or similar languages to automate content tasks and integrate with APIs.
• Practical experience applying LLMs to content workflows, including prompting, retrieval, grounding, and output evaluation.
• Experience with information architecture, content modeling, taxonomy, and metadata for navigation and machine retrieval.
• Technical depth to read code and APIs to verify accuracy and write working examples.
• Experience building RAG pipelines, AI assistants, or MCP servers (preferred).