Senior Software Development Engineer

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.

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 from financial loss and brand damage, securing every channel for our customers, partners, suppliers, and employees. Our world‑class engineering and machine learning turn massive, noisy signals into real‑time decisions that minimize risk while keeping traveler friction low.

What makes this work unique: in travel, risk doesn’t stop at checkout, 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’s hard and exactly why science and technology matter most.

If you’re energized by complex, high‑impact problems with no obvious answers, and want to shape the future of risk with AI on a global scale, join us. Let’s redefine how the world travels, safely, confidently, and at speed.

Role Summary

Lead the architecture and delivery of real‑time, AI‑powered fraud and abuse defenses on a global scale. 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 technical architecture and lead design and delivery of AI‑driven solutions for automated risk decisioning and remediation.
• Incorporate and integrate Generative and Agentic AI into fraud detection workflows, simplifying and modernizing the platform while reducing time to detect and mitigate attacks.
• Benchmark various vendor, open source and in‑house solutions for performance, cost and risk posture.
• Build, deploy, and operate ML in production; partner closely with Data Science/ML Scientists on features, experimentation, and monitoring.
• Establish clear SLOs, observability, and safety/rollback mechanisms; ensure security, privacy, and compliance are built in.
• Mentor other engineers and champion the use of AI within the organization.

Minimum Qualifications

• 9+ years of software engineering, including significant experience developing, deploying and operating ML/AI driven solutions in production.
• Demonstrable experience building, monitoring and debugging LLM and multi‑agent applications, with frameworks and platforms such as Lang Chain, Lang Graph, Langfuse, or equivalent.
• RAG‑based architecture experience, including data orchestration frameworks such as Llama Index, vector databases such as Pinecone, or equivalent.
• Exposure to various LLM providers such as OpenAI, Gemini, and Anthropic.
• Production ML experience (supervised/anomaly detection, feature pipelines, online inference, monitoring/retraining); ability to ship with Data Science/ML Science partners.
• Strong coding skills in one or more of Java/Scala/Go/Python.
• Familiarity with distributed cloud‑native engineering at scale (AWS, GCP, or Azure), microservices, API‑driven design, SQL/No
  
  SQL databases and data streaming/processing (Kafka, Flink, Spark).

Preferred Qualifications

• Proven experience building and operating either fraud and risk systems in production, or other similarly ML/AI heavy systems.
• Graph/sequence modeling or entity resolution at scale; device and behavioral signals.
• Track record reducing manual operations via automation and platform simplification.

Compensation

The total cash range for this position in Seattle is $ to $. Employees may increase pay up to $ based on sustained performance. Pay may vary by location, budget and individual experience.

Benefits

Ex…