Senior Engineering Manager, Loyalty

Expedia Group•Seattle, WA

1d•$184,500 - $295,000

About The Position

Expedia Technology teams partner with our Product teams to create innovative products, services, and tools to deliver high-quality experiences for travelers, partners, and our employees. A singular technology platform powered by data and machine learning provides secure, differentiated, and personalized experiences that drive loyalty and traveler satisfaction. The Loyalty Engineering organization powers how Expedia builds durable relationships with travelers worldwide. We build the systems behind continuous engagement, re-engagement, and re-acquisition, creating a growth flywheel that deepens traveler loyalty and drives measurable business impact across brands and markets. At the center of this sits your team, the Incentives platform, a full-stack system responsible for delivering billions of dollars in offers and perks to travelers every year. The Senior Engineering Manager, Loyalty role is at the intersection of platform engineering, AI innovation, and business growth strategy. You will lead the full-stack team that owns the Incentives platform, working closely with cross-functional partners across product, marketing, and business to scale one of Expedia's most commercially critical systems. The work here is highly visible. The decisions you make will directly shape how loyalty incentives drive growth for millions of travelers across Expedia's global portfolio.

Requirements

Bachelor’s Degree or Equivalent Level; Technical Degree Preferred.
8+ years of relevant professional experience and 3+ years of people management experience.
Experience leading full-stack software engineering teams delivering services and platforms in a complex product ecosystem.
Proven background in software engineering with strong capabilities in system design (including low-level design), API design, and data modeling for distributed, service-oriented or microservices-based systems.
Demonstrated ability to manage delivery for multiple concurrent initiatives, aligning engineering execution with product and business priorities across the loyalty domain or an equivalent business capability area.
Hands-on experience establishing and enforcing engineering standards around code quality, testing, deployment, monitoring, and reliability for production services.
Familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to real world products, including collaborating with specialized teams to integrate such capabilities into production services.

Nice To Haves

Experience building and scaling loyalty, membership, marketing or customer engagement platforms, at high scale and availability.
Familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to real world products, including safely integrating and operating AI/ML‑enabled solutions that improve loyalty outcomes, and guiding teams on practical, domain-specific use of these technologies.
Demonstrated success in leading engineering teams through periods of high growth, change, or complexity.
Track record of championing data-driven decision making and operational excellence for mission-critical systems.
High ownership mindset with a bias for action.

Responsibilities

Lead, develop, and retain a high-performing engineering team that delivers high-quality loyalty capabilities and services aligned to product and business goals.
Own end-to-end delivery for key loyalty services and platforms, ensuring system design, low-level design, API design, and data modeling meet performance, security, and reliability expectations.
Partner closely with Product, Architecture, Data, and other engineering teams to define and execute a technology roadmap for loyalty, balancing near-term delivery with long-term platform evolution.
Establish and continuously improve engineering best practices, including code quality, CI/CD, observability, incident response, and operational excellence for loyalty systems.
Drive data-informed decision making for loyalty features and services, using metrics, experimentation, and customer behavior insights to guide prioritization and technical trade-offs.
Foster a culture of innovation and safety around advanced technologies, including familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to real world products, and safely integrates and operates AI/ML‑enabled solutions that improve outcomes.