Lead AI Experience Engineer
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Job Description
Lead AI engineer designing agentic support experiences for Ticketmaster’s global live-event ticket marketplace. Establishing AI standards, evaluation practices, and technical direction for client and fan support.
Responsibilities:
- Provide technical leadership for agentic AI across the TM1 Client & Fan Support Engineering team
- Partner 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 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, production-ready solutions
- Define and monitor AI quality measures, including task completion, response quality, grounding, escalation accuracy, containment, customer satisfaction, and business outcomes
- Partner with Product, Client and Fan Support Operations, Data Science, Platform, QA, Security, and Knowledge Management
- Mentor AI Engineers through technical guidance, feedback, design sessions, and knowledge sharing
- Evaluate emerging AI technologies and recommend practical approaches to improve quality, delivery, and operational effectiveness
Requirements:
- 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 into AI decision logic and user experiences
- Experience designing guardrails, policy controls, escalation paths, failure handling, and responsible AI practices
- Experience defining AI evaluation frameworks and using interaction data, testing, and analytics to improve performance
- Knowledge of RAG, semantic search, enterprise knowledge systems, grounding, observability, and regression testing
- Working knowledge of APIs, cloud services, software architecture, integration patterns, and modern engineering practices
- Ability to lead complex initiatives, navigate ambiguity, and balance business value, customer experience, technical constraints, risk, and maintainability
- Strong communication, stakeholder management, systems thinking, and problem-solving skills
- Bachelor’s or master’s degree in relevant discipline, or equivalent practical experience (preferred qualification)
- Experience operating agentic AI solutions in production (preferred)
- Experience with conversational AI platforms, agent orchestration frameworks, prompt-management tools, or AI evaluation platforms (preferred)
- Experience in customer service, contact center, or high-volume digital support environments (preferred)
- Familiarity with Amelia, Zendesk, Five9, Salesforce, or comparable platforms (preferred)
- Knowledge of AI governance, privacy, security, accessibility, and multilingual support (preferred)
Benefits:
- Inclusive work environment
- Support to balance work and homelife
- Professional and personal development opportunities
- New experiences and learning from talented colleagues
- Equal opportunities regardless of gender, race, sexual orientation, religion, age, disability status, or caring responsibilities
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