AI Content Program Manager, Chatbot

HoneyBook is the leading AI-powered business management platform for service-based business owners. Designed to enhance - not replace - independent professionals. HoneyBook’s AI-powered tools help businesses attract leads, connect with clients, book projects, and manage payments more efficiently. With AI seamlessly integrated into every workflow, entrepreneurs can focus on their craft while scaling their businesses with confidence. Since its founding in 2013, HoneyBook has powered over 25 million client relationships and processed more than $12 billion in transactions, helping independent businesses grow faster and smarter.

Our culture is built on five core values that inform everything we do. We encourage collaboration, feedback, ownership, and maintain a growth mindset. We know experience comes in many forms - some visible on your resume, others not. No one candidate will be a 100% perfect match to our description, so if you thrive in a fast-paced, intellectually curious environment and have relevant experience, we encourage you to apply.

About the role

As an AI Content Program Manager, you’ll sit within the Knowledge & Instructional Content team (KIC) that supports both our members (customers) and our Support Specialists. You’ll own the strategy and execution of our support chatbot, the front line for how members get fast, accurate answers, and you’ll support the full lifecycle of the Help Center articles and internal Support documentation that feed it.

You’ll set the direction for how our chatbot resolves member issues, from what it should be able to handle to how content gets structured so it can act on it, and you’ll build the Help Center content and Support documentation that equip Support Specialists with clear, dependable guidance across every channel. From building new content to optimizing existing workflows, your work will directly influence the clarity, consistency, and effectiveness of our member and agent experiences. Every article you publish, update, or structure directly determines how members get fast, accurate answers. AI resolution is one of the most important levers the team owns, and you’re accountable for moving it. As chatbot resolution matures, you’ll set the strategy for how we prioritize and structure content investment across the AI resolution funnel.

Here are a few of the things you will do

• AI Resolution Strategy: Own the analysis of chatbot resolution data in partnership with Member Care and AI Operations, identify where content gaps are limiting AI resolution rates, drive the roadmap for what gets built, updated, or restructured next, and help evaluate whether a single-platform or multi-platform chatbot strategy best serves our members.
• Chatbot Build & Configuration: Work directly in our chatbot platform (currently Intercom) to configure and maintain our support chatbot, and use Claude Code to build and maintain the data connectors that power it.
• AI Process Innovation: Go beyond using LLMs for drafting, content gap analysis, and basic data synthesis. Identify where AI can change how the team works, and own the evaluation and rollout of new AI tools and workflows.
• App Development: Build functional internal tools using no-code/low-code platforms (such as Lovable) to solve real team friction points. You’ll ship internal tools frequently, with support and context from the team.
• AI-Driven Content Strategy: Utilize Large Language Models (LLMs) for drafting, brainstorming, and basic data synthesis to accelerate content production.
• Member-Facing Support: Support the creation, maintenance, and ongoing improvement of member-facing Help Center content that supports fast, accurate self-serve resolution.
• Technical Documentation: Write clear, actionable technical how-tos and process documentation that guide members and Support Specialists to the most efficient and effective resolution.
• Internal Governance: Help maintain internal Support documentation so it is clear, accurate, and structured for both human and AI-assisted resolution. In practice, this means writing procedures our Support bot can act on, documenting decision logic for connector builds, and incorporating QA findings into content revisions, as well as human-readable accuracy. The quality of this documentation is a direct input to how effectively AI resolves member issues at scale.
• Cross-Functional Collaboration: *Own th…