Senior Manager, Software Development Engineering

Expedia Expedia · Hospitality · Seattle, WA

Senior Manager, Software Development Engineering for Fraud & Risk at Expedia Group. This role focuses on leading the integration of Generative and Agentic AI into fraud detection workflows, modernizing the platform, and reducing detection/mitigation times. The role also involves owning platform architecture, technical operations, and partnering with Data Science/ML Scientists. Experience with RAG, LLMs, and multi-agent applications is preferred.

What you'd actually do

  1. Own your team’s platform architecture, design and delivery of solutions for automated risk decisioning and remediation.
  2. Hold a high bar for technical operations, establish clear SLOs, observability, and safety/rollback mechanisms for your team’s software.
  3. Lead the integration of Generative and Agentic AI into fraud detection workflows, simplifying and modernizing the platform while reducing time to detect and mitigate attacks.
  4. Advocate for the use of AI in improving engineering processes, productivity and the SDLC.
  5. Partner closely with engineering teams and Data Science/ML Scientists on features, experimentation, monitoring and delivery.

Skills

Required

  • 9+ years of software engineering
  • 2+ years in an engineering leadership role
  • distributed cloud-native engineering at scale (AWS, GCP, or Azure)
  • microservices and API-driven design
  • SQL/NoSQL databases
  • data streaming/processing technology (Kafka, Flink, Spark)
  • Java/Scala/Go/Python
  • guiding teams to achieve excellence in tech operations
  • ML-integrated systems
  • working with Data/ML Science partners
  • mentorship
  • coaching
  • helping engineers with career growth

Nice to have

  • building and operating fraud and risk systems in production
  • other similarly ML/AI heavy systems
  • reducing manual operations via automation and platform simplification
  • RAG-based architectures
  • LLMs
  • multi-agent applications

What the JD emphasized

  • Generative and Agentic AI
  • fraud detection workflows
  • risk systems in production
  • RAG-based architectures, LLMs and multi-agent applications

Other signals

  • leading integration of Generative and Agentic AI into fraud detection workflows
  • reducing time to detect and mitigate attacks
  • advocating for AI in improving engineering processes
  • partnering with Data Science/ML Scientists
  • building and operating fraud and risk systems in production
  • experience with RAG-based architectures, LLMs and multi-agent applications