AI Agents Manager: Customer Care

We power people’s progress.

At Preply, we’re all about creating life-changing learning experiences. We help people discover the magic of the perfect tutor, craft a personalised learning journey, and stay motivated to keep growing. Our approach is human-led, tech-enabled - and it’s creating real impact.

We’ve just reached unicorn status with a $150M Series D, accelerating our vision to transform education through human-led, AI-enhanced learning. Today, 100,000+ tutors teach 90+ languages to learners in 180 countries - and we’re only getting started. As a category-defining company, we’re shaping what the future of learning looks like at global scale.

Every Preply lesson sparks change, fuels ambition, and drives progress that matters. Joining Preply means helping define the future of education at global scale, and building something that truly matters for millions of people, every day.

Meet the team!

AI is no longer a side customer support channel at Preply, it is one of the main ones. Our customer-facing AI chatbot already handles most of our lower complexity support conversations, and we are doubling down on AI as the primary way learners and tutors get help. As AI becomes central to how support works, the shape of the team behind it has to change too: from one that answers questions to one that designs and continuously improves the system that answers them.

To do this well, we are building a dedicated AI chatbot team within Customer Care, structured around the four foundational roles needed to make AI agents perform: AI Operations, Knowledge Management, Conversation Design, and Support Automation. As AI Agents Manager (Customer Care), you will lead this team end-to-end, the equivalent of an AI Operations Lead with full ownership of the function. You will report directly to the Director of Customer Care and manage AI Operations / Automation Specialists, AI Content Knowledge Managers, and also get direct support and coverage from the Customer Care product, engineering, and design teams.

This is a player-coach role. You will roll up your sleeves to analyze AI performance, refine content, and debug handoffs, while also coaching the team through an entirely new way of working. You will treat the AI Agent/Chatbot as a teammate to manage and a product to improve, not just a tool to monitor. Your immediate focus is to elevate the Customer Care chatbot, improving resolution and deflection, but above all the quality and customer experience of every AI interaction. Over time, you will expand into more proactive AI agents/chatbot (built on Intercom FinAI and similar platforms) for use cases beyond reactive support.

What you’ll be doing

Own the end-to-end performance of Preply's customer-facing AI agents/chatbot: resolution rate, deflection, and most importantly the quality and CX of every AI conversation

Lead and develop a multi-disciplinary team across the four pillars of AI agent performance: AI Operations, Knowledge Management, Conversation Design, and Support Automation: setting direction, coaching, and unifying them around a shared roadmap

Drive the day-to-day performance loop: track AI quality, tune behavior, prioritize fixes, and drive continuous iteration. Making small improvements compound into meaningful gains

Treat the AI Agent as a product: own its roadmap, its quality standards, and its evolution; not as a tool to monitor, but as a teammate to manage and improve

Drive the short-term performance improvement of the Customer Care chatbot across every lever that matters: knowledge quality and coverage, conversation design and tone, intent recognition, flow logic, guardrails, handoff design, and the workflows the AI can execute

Define and own the AI agents roadmap, prioritizing use cases beyond reactive support — including proactive AI agents for tutor and learner journeys built on Intercom FinAI and adjacent platforms

Through your team, ensure the AI Agent has the right inputs to succeed: accurate and well-structured knowledge content, well-designed conversation flows that match Preply's brand voice, and backend workflows that let the AI take action, not just respond

Operate as the central node across a wide stakeholder map: work hand-in-hand with the Customer Care Product & Engineering teams (to build and ship AI capabilities), the Customer Care Data team (for performance analytics, conversation analysis, and experimentation), the Design team (for AI experience and brand consistency), and the CX team (for the policies and rules behind every automation) \u2014 plus broader Product, Marketing, and Supply teams for cross-functional use cases

Define safety boundaries, escalation rules, and quality standards for every AI agent, making sure AI handoffs to humans happen at the right moment, for the right reasons

Stay ahead of the curve on conversational AI platforms and capabilities (Intercom FinAI, LLM-based agents, agentic frameworks, RAG, tool use), evaluating what is worth adopting and what is hype, and owning build vs. buy decisions

Own AI performance reporting end-to-end: resolution rate, deflection, CSAT on AI conversations, containment, and the operational KPIs that link AI quality to Customer Care outcomes

Collaborate closely with the Human Support function so AI and human support operate as one seamless experience for customers

What you need to succeed

5+ years of experience implementing or managing AI / conversational AI / chatbot products in a customer-facing context, with at least 2 years leading a team

Deep, hands-on experience with conversational AI platforms, ideally Intercom Fin / FinAI, but also relevant: Ada, Forethought, Decagon, Sierra, or equivalent LLM-based agent platforms

Proven track record improving AI chatbot performance across the full stack of levers: knowledge content, conversation design, intent and flow logic, guardrails, handoff design, and backend actions / workflows

Strong understanding of how modern AI agents work under the hood, LLMs, retrieval-augmented generation, tool / function calling, agentic workflows, enough to challenge vendors and make sound build vs. buy decisions

Demonstrated ability to balance the technical and the customer-experience side of AI: you care about resolution rate, but you care equally about how the AI sounds, how it handles ambiguity, and how it makes the customer feel

Player-coach mindset, comfortable rolling up your sleeves to analyze performance, refine content, and debug handoffs, while also coaching and developing the people doing that work

Experience working in a customer support, contact centre, or customer experience environment, you understand support operations, KPIs (CSAT, AHT, deflection, resolution), and how AI changes them

Strong people management skills with experience leading multi-disciplinary teams (knowledge specialists, designers, technical implementers, AI ops)

Excellent stakeholder management and cross-functional communication skills \u2014 comfortable operating as the connective tissue between Product, Engineering, Data, Design, CX policy, and business teams, and explaining AI capabilities and limitations to non-technical audiences

Data-driven mindset with strong analytical skills; comfort building dashboards, reading conversation analytics, and turning patterns into action

Builder's mentality, energized by a fast-moving space, comfortable with ambiguity, and motivated by the chance to shape AI at the heart of a 50M+ user platform

Nice to Have

Hands-on configuration experience with Intercom Fin or Intercom's AI agent / workflow tooling

Background in conversation design, UX writing, or knowledge management for AI products

Experience launching proactive AI use cases (outbound messaging, in-product AI assistants, lifecycle AI agents), not just reactive support bots

Familiarity with AI evaluation frameworks, prompt engineering, and quality scoring methodologies for conversational AI