Software Development Engineer II

Expedia•Seattle, WA

About The Position

At Expedia Group, we help travelers explore the world, one journey at a time. As a global travel company powered by passionate people, trusted partnerships, and leading technology, we connect travelers, partners, and advertisers through our consumer brands, B2B network, and travel advertising business. Here, you'll do meaningful work that helps millions of people discover, book, and experience travel with more ease, confidence, and joy. Our five Behaviors-Traveler First, Think Big, Operate with Excellence, Ownership Mindset, and Succeed Together-help foster a supportive environment where people can grow their careers and have the flexibility, benefits, and support to do their best work. Join us and build for travelers everywhere. Introduction to Team Expedia Group brands power global travel for everyone, everywhere. We design cutting-edge tech to make travel smoother and more memorable, and we create groundbreaking solutions for our partners. Our diverse, vibrant, and welcoming community is essential in driving our success. This Software Development Engineer II role is part of the Distribution and Supply Tech - Inventory Team team which sits within our Technology division. The team enables suppliers to sell and distribute their inventory by managing lodging products, rates, availability, and related inventory data, and by distributing that information to pricing and reservation services so travelers can find and book suitable options. In this role, you will deliver reliable software components and services that support scalable, high-quality travel experiences for travelers, partners, and Expedia Group.

Requirements

Bachelor’s degree in Computer Science or a related technical field; or equivalent related professional experience.
2+ years of relevant professional experience.
Demonstrated ownership of well-defined services, components, or features across design, implementation, quality, deployment, and operational support within a product or domain area.
Proficiency in software engineering fundamentals, including data structures, algorithms, system design (LLD), API design, and data modeling, with experience applying these concepts in production systems.
Hands-on experience with modern backend technologies and service architectures, as well as familiarity with AI-driven tools or workflows that enhance developer productivity or product capabilities.

Nice To Haves

Experience contributing to multi-service backend architectures, including well-structured APIs, data models, service integrations, and reliable data flows.
Exposure to improving high-traffic or customer-facing systems through performance optimization, resilience improvements, reliability engineering, or backend optimization.
Practice with operational excellence, including instrumentation, logging, metrics, observability, alerting, on-call participation, and incident response.
Experience using experimentation, feature flags, A/B testing, analytics, or service metrics to guide technical decisions and measure the impact of delivered work.
Experience integrating or extending AI/ML-enabled capabilities across backend services, including responsible use of AI-driven components and AI tooling for development, testing, code quality, or operations.

Responsibilities

Design, build, and evolve reliable backend services, including system design (LLD), API design, and data modeling for scalable, secure, and maintainable solutions.
Implement high-quality production code and supporting service components, emphasizing automated testing, observability, performance, and operational excellence.
Collaborate with product, design, and partner engineering teams to translate customer and business requirements into robust backend solutions, reusable service integrations, and well-structured data flows.
Own and improve the end-to-end lifecycle of services and features, including development, testing, deployment, monitoring, troubleshooting, and incident resolution.
Apply data, metrics, experimentation, and analytics to prioritize work, validate hypotheses, and continuously improve service performance, reliability, and user experience.
Safely integrate and operate AI/ML-enabled solutions that improve outcomes, including familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to real world products.