AI Operations Manager - AI Builder

Expedia•Seattle, WA

22h•Hybrid

About The Position

Expedia Group’s Traveler and Marketplace Operations team is responsible for shaping how AI is used in customer service, including defining quality standards for AI-handled traveler contacts, designing handoffs between automated systems and people, and building tools that help operations leaders understand service performance. The team partners with Product and Technology and also builds tools directly, including systems that score property quality risk and surface traveler-experience issues from conversations and cases. The AI Operations Manager is a broad, cross-functional role suited to someone who can work independently toward outcomes, move between hands-on building and strategic collaboration, and adapt as priorities change. The role builds and ships tools, prototypes AI-enabled solutions, translates operational problems into well-scoped work, represents operations in AI programs, advises leaders, coordinates work across teams, guides partner-based AI builders, and helps operations teams adopt new tools.

Requirements

Bachelor’s degree in business, analytics, computer science, or a related field, or equivalent related professional experience.
At least 5 years of experience in contact center or service operations, business operations, or a comparable strategic, analytical, and operational role.
Ability to interpret data in its operational context.
Hands-on ability to build: write database queries and read, modify, and review Python sufficiently to understand what is being shipped. Professional software developer experience is not required.
Track record of taking ideas from concept to working prototype to adoption, with clear impact on operational or business outcomes.
Experience defining how to measure success, including success metrics, guardrails, and instrumentation.
Excellent qualitative and quantitative analytical skills and proficient communication skills, including synthesizing complex detail into precise, accessible insights for senior audiences.
Ability to prioritize, manage several workstreams, build relationships across a wide range of people, and influence cross-functionally without relying on authority.
Comfort with ambiguity and a self-directed, outcome-oriented approach; ability to work collaboratively and autonomously, stay organized as priorities shift, and finish hands-on work.
Experience building with generative AI, including retrieval-based systems, prompt and context design, agent workflows, or model evaluation.
Collaborative working style, including listening for underlying concerns, adapting explanations to the audience, and keeping colleagues informed.
Familiarity with large enterprise data platforms and practical tasks such as obtaining access, understanding schemas, and troubleshooting data issues.

Nice To Haves

Experience supervising AI-assisted development, including reviewing generated code and determining when to trust or verify it.
Experience leading projects with technical and business contributors and leading operational change or enablement programs, formally or informally.
Background in analytics, data science, or software development, including experience gained while primarily working in operations.
Experience with conversational or voice AI, agent assistance tools, or automated quality monitoring in a service environment.
Familiarity with enterprise deployment and delivery platforms.

Responsibilities

Build and ship end-to-end tools, including applications, AI-powered analysis, and data pipelines, to provide operations leaders with a broad view of quality and traveler experience.
Rapidly prototype using large language model APIs, AI-assisted development tools, and internal data platforms to demonstrate value before committing to larger engineering investment.
Translate open-ended operational problems into clearly scoped work with defined data sources, safeguards, and success criteria.
Represent operations in cross-functional AI programs by translating agent and traveler experiences into requirements, guardrails, and measures of accuracy.
Produce analysis and recommendations for senior leaders, proactively surfacing risks and opportunities and advising on feasibility, effort, and sequencing.
Own the operating rhythm for the work by preparing agendas, facilitating discussions, capturing decisions and actions, and following issues through to closure across platform, data, and security teams.
Guide and review the work of a small group of partner-based AI builders, establishing standards for quality, testing, and safe use of AI-assisted development.
Help operations teams adopt tools by building trust and fluency so prototypes become part of day-to-day work.