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 have 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-charged environment and have similar experience to what we are looking for, we encourage you to apply.
As our CX AI Operations Lead, you’ll drive the technology and tooling that scale and automate Member (customer) Care at HoneyBook. From conversation design to bot training, flow optimization to analytics infrastructure, you’ll build systems that solve real member problems efficiently, and at scale. With a focus on emerging AI tools, you’ll act as both architect and operator of our CX automation programs, bringing a rigorous, experiment-driven approach to improving performance. You’ll collaborate closely with Product, Engineering, and Member Care to bring new capabilities to life.
This role is hybrid to our SF office, 3 days per week.

• Own the configuration and optimization of our CX automation systems, including AI bots, workflows, and knowledge tools. You’ll ensure performance, quality, and alignment with member experience goals.
• Design and implement automation flows that include branching logic, fallback handling, handoff pathways, and prompt tuning across our digital support surfaces.
• Improve system-level performance of tools like Intercom Fin by running structured experiments, refining flow logic, and driving containment, resolution rate, and CSAT outcomes.
• Build the infrastructure to support digital experimentation, including reporting pipelines, test design, and performance benchmarks.
• Define and track key AI performance metrics (ex. resolution rate, deflection, satisfaction), ensuring clean instrumentation and regular reporting to key stakeholders.
• Collaborate with Product, Engineering, and Support teams to align on automation strategy, launch timelines, and shared outcomes.
• Contribute to the Voice of the Customer program, surfacing systemic issues, tagging content gaps, and closing the loop between AI signals and team insights.