Principal AI Builder Product Manager

Introduction to the Team:

Expedia Group powers travel for everyone, everywhere. As AI becomes core to how travelers plan, book, and manage their trips, our ability to rapidly explore, prototype, and ship new AI capabilities becomes essential. You will help build the next generation of AI-powered experiences and the underlying patterns that ensure every experience meets a high standard of clarity, accuracy, and trust.

The Core AI Experiences team defines how Expedia Group builds AI. We create reusable components, orchestration patterns, and quality bars that help teams across the company turn frontier-model capabilities into delightful, reliable customer experiences. We partner with product, engineering, design, and data science teams supporting shopping, servicing, and other key journeys.

In this role, you will be a hands-on AI builder PM. You will prototype new AI experiences using third‑party and internal models, evaluate emerging capabilities, and lead the most promising ideas from experiment to production at scale. Your work will influence AI-powered experiences across Expedia Group and set the bar for what “great” looks like in applied AI.

In this Role, you will:

• Identify high-impact traveler and partner problems that can be unlocked by AI, and frame them as clear, testable product bets.

• Rapidly prototype end‑to‑end AI experiences using available LLMs and tools (e.g., prompt design, tool/function calling, retrieval, simple UIs) to validate value and feasibility.

• Evaluate new capabilities from frontier labs and internal platforms, and translate them into concrete product concepts, demos, and proof‑of‑concepts.

• Partner closely with engineering, data science, and design to take successful prototypes to production, including instrumentation, experimentation, guardrails, and ongoing quality improvements.

• Define reusable patterns and primitives (e.g., explanations, preview/approve/undo flows, context continuity) that can be adopted across teams and surfaces.

• Establish clear success metrics and experimentation plans for AI features, and use data and user feedback to guide iteration and prioritization.

• Communicate clearly with senior leaders and cross‑functional partners, bringing structure and clarity to ambiguous technical and product spaces.

• Share learnings, playbooks, and best practices so that prototyping and AI‑first thinking become part of how product teams across Expedia Group operate.

Minimum Qualifications:

• 10+ years of product management experience building consumer or platform products, including meaningful work with AI, ML, or technically complex systems.

• Strong technical depth and experience partnering with engineering and DS/ML teams; comfortable discussing system design, data flows, tradeoffs, and constraints.

• Hands‑on ability to prototype: capable of using APIs/SDKs from major LLM providers and writing simple code (e.g., Python or TypeScript/JavaScript) to stitch together prompts, tools, and basic interfaces.

• Proven track record of taking 0→1 product ideas from concept through prototype to launched features, with clear impact on customer and business outcomes.

• Experience with metrics, experimentation, and evaluation (e.g., A/B testing, success metrics definition, instrumentation, or system reliability).

• Exceptional written and verbal communication skills, with the ability to make complex technical topics accessible and to drive alignment across senior cross‑functional stakeholders.

Preferred Qualifications:

• Experience building or shipping AI/LLM-powered user experiences (e.g., conversational agents, copilots, recommendations, search, automation, or decision-support tools).

• Familiarity with LLM behavior and ecosystems: prompt engineering, tools/function calling, retrieval/RAG, embeddings, and basic evaluation techniques.

• Background in software engineering, data science, or ML (professional experience or equivalent technical projects), even if you have primarily worked as a PM.

• Understanding of trustworthy AI principles, including safety, bias, privacy, and failure‑mode analysis, and how to apply them in product design.

• Experience building frameworks, tools, or platforms that scale across multiple teams or products in a large organization.