AI Support Delivery Product Manager

Preply Inc.

Barcelona, Spain

27 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience required

2 years minimum

Working hours

Regular working hours

Job source

www.jobleads.com

Tech stack

Artificial Intelligence System Configuration Software Debugging Knowledge Management Performance Tuning Chatbots Retrieval-Augmented Generation Large Language Models Prompt Engineering Backend Virtual Agents

Job description

Own the end-to-end performance of Preply’s customer-facing AI agents/chatbot: resolution rate, deflection, and quality and CX of every AI conversation
Lead and develop a multi-disciplinary team across 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
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 short-term performance improvement of the Customer Care chatbot across all levers: 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
Ensure the AI Agent has the right inputs to succeed: accurate and well-structured knowledge, 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 - Customer Care Product & Engineering, Customer Care Data, Design, CX, 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 and for the right reasons
Stay ahead of the curve on conversational AI platforms and capabilities, evaluating what is worth adopting versus hype, and owning build vs. buy decisions
Own AI performance reporting end-to-end: resolution rate, deflection, CSAT on AI conversations, containment, and operational KPIs linking 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

Requirements

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 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: care equally about resolution rate and how the AI sounds, handles ambiguity, and makes the customer feel
Player-coach mindset, comfortable rolling up sleeves to analyse performance, refine content, debug handoffs, while coaching and developing the people doing the work
Experience working in a customer support, contact centre, or customer experience environment - 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 - comfortable operating as 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, energised by fast-moving space, comfortable with ambiguity, and motivated by the chance to shape AI at the heart of a 50M+ user platform, * 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
Experience in marketplace, EdTech, or subscription-based businesses