Remote Expedia Software Engineer Jobs (NOW HIRING)

Introduction to the Team:

Our Technology Team partners with teams across Expedia Group 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.

At Expedia Group Fraud & Risk (EFR), we are the guardians of marketplace trust. We protect EG fromfinancial lossand brand damage, securing every channel for our customers, partners, suppliers, and employees.Our world classengineering and machine learning turn massive, noisy signals intoreal timedecisions that minimize risk while keeping traveler friction low.

What makes this work unique: in travel, riskdoesn'tstop atcheckout,it spans the entire journey. The global ecosystem is vast and fragmented, control points are scarce, and every leg introduces new unknowns. Our mission is bold: deliver a fully trusted journey from purchase to safe return home.That'shard and exactly why science and technology matter most.

Ifyou'reenergized by complex,highimpactproblems with no obvious answers, and want to shape the future of risk with AI on a global scale, join us.Let'sredefine how the worldtravels,safely, confidently, and at speed.

Lead the architecture and delivery of real-time, AI-powered fraud and abuse defenses on a global scale. You will design cloud-native decisioning and automated remediation systems, simplify our platform, and align cross-functional teams to measurable outcomes.

In this role, you will:

• Own end-to-end architecture for low-latency risk decisioning (signals + rules + models) and automated remediation

• Build, deploy, andoperateML in production; partner closely with DS/ML on features, experimentation, and monitoring

• Simplify and modernize the platform (streaming/data pipelines, microservices, CI/CD, configuration-driven controls) to speed safe iteration

• Drive build-vs-buy evaluations and benchmark vendors against in-house solutions for performance, cost, and risk posture

• Establish clear SLOs, observability, and safety/rollback mechanisms; ensure security, privacy, and compliance are built in

• Mentor senior engineers and align Product, Ops, Security, and Compliance on roadmap and outcomes

• Communicate clearly with executives and engineering: distill strategy, make tradeoffs explicit, and document decisions.

Minimum Qualifications:

• 10+ years of software engineering, including 4+ years leading architecture for real-time, high-scale systems

• Proven experience building and operating fraud/risk systems in production (e.g., booking, payments/chargebacks, ATO, content/supplier integrity), with measurable impact on losses, false positives, and manual effort

• Production ML experience (supervised/anomaly detection, feature pipelines, online inference, monitoring/retraining); ability to ship with DS/ML partners

• Cloud-native engineering at scale (AWS, GCP, or Azure): event-driven services, data/stream processing, observability,costand reliability best practices

• Strong coding skills in one or more of Java/Scala/Go/Python; microservices, APIs, and infrastructure-as-code

• Security, privacy, and regulatory fundamentals for sensitive data and risk decisioning

• Experience with executive communication: can brief executives, translate strategy into actionable engineering plans, and align teams

Preferred Qualifications:

• LLM/agentic techniques applied to fraud (e.g., investigation assist, pattern discovery, automated playbooks) and retrieval over enterprise data

• Graph/sequence modeling or entity resolution at scale; device and behavioral signals

• Track recordreducing manual operations via automation and platform simplification

• Hands-on with experimentation platforms and real-time rules/model simulation/back testing

• Deep cloud cost/performance tuning and capacity planning

• Marketplace, travel, or e-commerce experience