Sr Lead, AI & Automation - Customer Support

About the Role

Hi, I'm Kirsten Stuart, Director of Customer Success Operations, and I've been at Jane for 8 years.

Our Customer Success Operations team is the engine behind one of the most celebrated support experiences in healthcare tech. We sit at the intersection of technology, people, and purpose, building the systems, tools, and intelligence that allow our Support team to show up for healthcare practitioners in a way that feels genuinely human and consistently delightful. From knowledge ecosystems to real‑time operations, we're shaping what world‑class support looks like as Jane grows.

On a more personal note, when I'm not thinking about support strategy, you can usually find me working out or walking my dog. Movement helps me reset, stay curious, and show up with energy, something I try to bring to my work every day.

This role is a hybrid builder-and‑leader position. You'll be hands‑on, designing and shipping agents that remove friction from our team's workflows, while also leading a small team and partnering closely with stakeholders across the Customer Team and AI Transformation Team to make sure the tooling actually lands. The goal is simple but meaningful: free our teams from manual, high‑friction work so they can spend their time on the relationships and high‑value work that matter most.

• Design, build, and ship agents that solve specific friction points in the Customer Team workflows, architecting how they work rather than just configuring off‑the‑shelf tools.
• Continuously identify where friction lives across the support organization (repetitive tasks, slow lookups, manual handoffs) and turn that into an agent roadmap.
• Own performance and quality of AI tooling in production: accuracy, tone, resolution rates, and where a human needs to step back in.
• Stay close to what's emerging in LLMs, agent frameworks, and semantic search.

• Work with the AI Transformation team to align on architecture, capability, and what's feasible now versus later.
• Partner with Support stakeholders and the team themselves to understand where the real friction is.
• Bring in subject matter experts across Support Ops to validate agent behaviour in their domain before it ships.
• Represent Support's needs in company‑wide AI conversations, and bring company AI direction back to Support.

• Own the knowledge base and internal documentation, keeping it accurate and well‑governed as the substrate agents and Drivers both rely on.
• Build content and taxonomy practices that make information usable by both humans and AI, not just searchable.
• Use support data and agent performance to find and close knowledge gaps.

• Own how customers and prospective customers find answers to their questions, end to end, across guides and the AI answer tool.
• Set and hold the exceptional quality bar for those answers: accuracy, tone, and whether the response actually resolves the question. Ensuring results are as good as our world‑class team.
• Analyze what customers and prospects are asking (queries, search terms, unresolved questions) to surface patterns worth acting on.
• When the answer is missing or wrong, that's a knowledge or content gap to close. When the real fix is in the product itself, that's feedback to route to Product.
• Partner with Product and Product Marketing so recurring "not yet customer" questions inform what we build and how we message it, not just what we document.

• Lead a small team of knowledge and AI enablement experts: set priorities, run 1:1s, and grow their skills, including agent‑building capability.
• Build a team that can move between deep AI/technical work and the people side of Support without losing either.

• Track quality metrics for AI‑assisted and self‑service answers, including accuracy and CSAT, to make sure automation holds the same bar as our team.
• Track efficiency metrics, including deflection rate, average handle time, and Driver time saved, to show where friction has actually been removed.
• Track downstream business impact, including retention and…