Senior Software Engineer - Distribution & Supply

Expedia Group•Seattle, WA

14d•$184,500 - $295,000

About The Position

At Expedia Group, our Distribution and Supply organization builds the core systems that power the global travel marketplace. We enable travelers to discover, compare, and book travel while helping partners optimize pricing, inventory, and visibility across the platform. Our platforms support hotels, vacation rentals, flights, cars, packages, and cruises across Expedia Group brands. Every day, our systems process trillions of pricing requests, powering experiences for hundreds of millions of travelers worldwide. We are looking for a Senior Software Development Engineer to help build and scale the next generation of pricing and marketplace infrastructure. In this role, you will design and operate highly available, low-latency distributed systems that ensure travelers always see the best possible deals while enabling partners to maximize their reach and revenue. This is a high-impact role where you will own critical services that directly influence traveler experience and partner success across the Expedia ecosystem. The systems you build will power the core marketplace infrastructure for global travel, influencing how millions of travelers find value and how thousands of partners optimize their business. You’ll work on mission-critical systems operating at massive scale, solving complex distributed systems problems while helping shape the future of travel technology.

Requirements

Bachelor’s degree in Computer Science or a related technical field; or Equivalent related professional experience.
8+ years of relevant professional experience.
Demonstrated ownership of one or more services or components, including responsibility for technical design, implementation, quality, and operational health.
Proficiency in system design (LLD), API design, and data modeling, with the ability to design for scalability, reliability, and maintainability.
Experience with service-oriented or microservices architectures, including automated testing, continuous integration/continuous delivery (CI/CD), and production monitoring practices.

Nice To Haves

Experience designing and evolving large-scale, distributed systems or high-traffic services, including performance tuning, capacity planning, and resilience engineering.
Track record of providing technical leadership within a team, including reviewing designs and code, mentoring other engineers, and influencing engineering best practices across services or domains.
Deep experience with observability and operational excellence, including metrics, logging, alerting, incident response, and post-incident analysis to drive long-term improvements.
Hands-on experience integrating AI/ML‑enabled features or services safely into production systems, including working with AI/ML platforms, SDKs, or APIs and managing associated risks such as quality, security, and misuse.
Familiarity with AI-driven systems, tools, or workflows for accelerating development (such as code generation, intelligent testing, or operational insights), and applying these responsibly to improve engineering productivity and product outcomes.

Responsibilities

Design, build, and own high-quality, scalable, and resilient software services and components, including system design (low-level design), API design, and data modeling aligned to Expedia Group engineering standards.
Lead end-to-end implementation of complex features and services across the full software development lifecycle, from technical design and coding through testing, deployment, and ongoing operational support.
Drive technical direction within your team by evaluating trade-offs, making data-informed decisions, and setting engineering best practices for code quality, observability, testing, and performance.
Collaborate closely with product, design, and partner engineering teams across multiple domains to deliver integrated solutions that meet functional, reliability, and scalability requirements.
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.
Proactively identify, debug, and resolve production issues, improve system reliability, and reduce operational toil through automation, monitoring, and continuous improvement initiatives.