Senior Software Development Engineer (GenAI, Agentic AI)

Expedia Group•Seattle, WA

8d•$184,500 - $295,000

About The Position

Expedia Group is seeking a Senior Software Development Engineer specializing in Generative AI and Agentic AI. This role is within the Expedia Group Fraud & Risk (EFR) team, which is responsible for protecting the company from financial loss and brand damage by securing all channels for customers, partners, suppliers, and employees. The EFR team uses world-class engineering and machine learning to make real-time decisions that minimize risk while maintaining low traveler friction. The unique challenge in travel risk is that it spans the entire journey, not just at checkout, across a vast and fragmented global ecosystem. The mission is to deliver a fully trusted journey from purchase to safe return home, which requires significant advancements in science and technology. This role offers the opportunity to redefine how the world travels safely, confidently, and at speed by leveraging AI on a global scale.

Requirements

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 LangChain, LangGraph, Langfuse, or equivalent.
RAG-based architecture experience, including data orchestration frameworks such as LlamaIndex, 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/NoSQL databases and data streaming/processing (Kafka, Flink, Spark).

Nice To Haves

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.

Responsibilities

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.