Lead, Product Documentation and Knowledge Operations

The Role

Key Responsibilities:

• The documentation operating model - end to end: intake, review, approval, publishing, maintenance, and health metrics. You own release notes and changelogs hands-on from day one and build the workflow that makes them consistent and repeatable.
• Product documentation standards - structure, voice, taxonomy, metadata, templates, versioning, source-of-truth governance, and AI-ready content requirements.
• Confluence governance and content architecture - you own the top-level information architecture, taxonomy, and governance standard for the instance. Product documentation is your primary domain; other functions publishing to Confluence (including Product Comms) conform to the standard you set.
• Workflow integration - connect documentation to Jira, Confluence, quarterly launch readiness, and required stakeholder reviews, in partnership with Product Operations and P&T leadership.
• Responsible-AI documentation practice - source traceability, approved input usage, hallucination checks, human review, compliance review paths, and accountable publishing decisions.
• Downstream trust and reuse - ensure Learning Services, Marketing, Implementation, Markets, Enablement, Support, and Client Success consume one trusted source rather than rebuilding product truth. Run periodic audits for freshness, findability, source alignment, and reuse readiness.
• The team, as the function scales — hiring, onboarding, coaching, prioritization, capacity planning, and quality standards for technical writers.

Requirements:

• Hands-on experience writing release notes, changelogs, and product or technical documentation - precise, economical, and accurate under deadline.
• Experience setting documentation standards and governance and scaling structured-content practices; mentoring or leading writers is a plus at this stage and expected as the function grows.
• Strong audience judgment: how product knowledge should be tailored, governed, and reused across product, engineering, and customer-facing teams.
• Comfort operating without a runbook - you create the structure, decision rights, operating rhythms, and governance the function needs.
• Fluency in Jira and Confluence, including how product and engineering teams use them to track work and connect it to structured knowledge.
• Familiarity with AI-assisted content workflows, semantic search, retrieval-augmented generation, and structured/AI-ready content - plus the judgment to use AI to accelerate the work without sacrificing accuracy, source validation, human accountability, or compliance.
• Ability to recognize when content needs review from Legal, Privacy, Security, or AI Trust.
• Nice to have: familiarity with APIs, SDKs, feature flags, versioning, integrations, or enterprise SaaS architecture; experience documenting complex B2B SaaS in insurance, automotive, claims, repair, payments, analytics, workflow, or AI environments.

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Preferred Qualifications

• Experience setting documentation standards and governance and scaling structured-content practices; mentoring or leading writers is a plus at this stage and expected as the function grows.
• familiarity with APIs, SDKs, feature flags, versioning, integrations, or enterprise SaaS architecture; experience documenting complex B2B SaaS in insurance, automotive, claims, repair, payments, analytics, workflow, or AI environments.
• A video interview is required for this position. Video interviews are transcribed. Transcriptions are retained and may be reviewed by CCC and our recruiters. Candidates are not permitted to use generative AI or automated assistance during the interviews unless explicitly allowed by the interview team for a specific exercise. Our Job Applicant Privacy Notice is available HERE.