Live Nation Entertainment
Lead AI Experience Engineer (Remote, United Kingdom)
United Kingdom · Remote
About this role
Job Summary: JOB DESCRIPTION – Lead AI Experience Engineer Location: Remote, United Kingdom Division: Ticketmaster Contract Terms: Fulltime THE TEAM The TM1 Client & Fan Support Engineering team builds and operates the intelligent, scalable technology that supports Ticketmaster’s client and fan service experiences. The team develops AI-powered support experiences, automation capabilities, integrations, and platform services that help clients and fans resolve issues quickly and confidently. We work closely with Product, Client Support, Fan Support, Knowledge Management, Data Science, Platform Engineering, Quality Assurance, Security, and other technology teams to deliver reliable and measurable outcomes. As our capabilities evolve from traditional conversational automation toward agentic AI, the team builds intelligent services that combine large language models, natural language understanding, enterprise knowledge, business logic, and operational systems. THE JOB Ticketmaster is seeking an experienced Lead AI Experience Engineer to provide technical leadership for the design and evolution of agentic AI services within the TM1 Client & Fan Support Engineering team . This role is responsible for defining how AI agents understand client and fan needs, maintain context, reason through complex scenarios, apply business rules, use available data and tools, and safely complete support tasks. The Lead AI Engineer will establish the methods, reusable patterns, quality expectations, and evaluation practices used by the AI Engineering team. The position combines agentic AI design, conversational intelligence, Natural Language Understanding, business-process modeling, AI evaluation, and technical leadership. The successful candidate will work closely with the Engineering Manager, Product Managers, AI Engineers, Client and Fan Support Operations, Data Science, and Platform teams to translate business requirements into scalable and trustworthy AI behaviors. WHAT YOU WILL BE DOING Provide technical leadership for agentic AI across the TM1 Client & Fan Support Engineering team, partnering with the Engineering Manager to define technical direction and strengthen the team’s AI capabilities. Lead the design of intelligent AI experiences that understand client and fan needs, apply business rules, maintain context, use available tools and data, and safely complete support tasks. Translate business processes, service policies, and customer journeys into agent behaviors, decision logic, conversational patterns, and autonomous workflows. Establish reusable patterns and standards for prompts, NLU, context management, guardrails, retrieval, tool use, evaluation, documentation, and human handoff. Conduct design and quality reviews, identify risks, and guide AI Engineers in delivering reliable, maintainable, and production-ready solutions. Define and monitor AI quality measures, including task completion, response quality, grounding, escalation accuracy, containment, customer satisfaction, and business outcomes. Partner across Product, Client and Fan Support Operations, Data Science, Platform, QA, Security, and Knowledge Management to align AI solutions with business, customer, and technical needs. Mentor AI Engineers through technical guidance, feedback, design sessions, and knowledge sharing. Evaluate emerging AI technologies and recommend practical approaches that improve quality, delivery, and operational effectiveness. WHAT YOU NEED TO KNOW (or TECHNICAL SKILLS) Significant experience designing and leading conversational AI, intelligent assistant, Generative AI, or agentic AI solutions. Deep understanding of LLMs, prompt engineering, agent behavior, reasoning patterns, context management, memory, tool calling, and workflow orchestration. Strong expertise in NLU, intent and entity modeling, semantic understanding, dialogue management, clarification strategies, and conversational design. Experience translating business rules and operational workflows
Skills and categories
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