Software Engineer Fraud Detection Jobs in Renton, WA

Principal Product Manager,Fraud & Risk Platform

Introduction to the Team:

The Product Team creates high-quality end-to-end experiences for travelers, partners, and Expedia Group. Our focus on customer-centric innovation enables us to develop products that build loyalty and repeat business. We partner closely with teams across Expedia Group to drive growth and achieve results for our customers and the company.

We'relooking for a highly influential individual contributor to architect the long-term strategy for our fraud prevention and risk management products across the diverse, global travel ecosystem. This role will spearhead complex, cross-functional initiatives that integrate advanced AI/ML detection capabilities, balance fraud loss reduction against customer friction, and protect the business while enabling growth. This leadership role demands strategic acumen, deep technical fluency, and a collaborative spirit to safeguard travel experiences globally.

In this role, you will:

• Define and evolve the long-term product strategy and vision for fraud prevention and risk management capabilities across a complex, global travel ecosystem, ensuring alignment with organizationalobjectives.

• Drive an integrated roadmap for a suite of fraud and risk products thatbalancesfraud loss reduction, customer friction, conversion, and operational cost, securing buy-in from cross-functional partners.

• Partner closely with engineering and data science leaders to advance the technical foundation of fraud detection and risk-scoring systems, including AI/ML-driven anomaly detection, behavioral analytics, and pattern recognition.

• Own key fraud and risk performance metrics such as fraud loss rate, false-positive rate, chargeback ratio, and approval/friction rates, making data-driven decisions on build-vs-buy, vendor tooling, and lifecycle evolution of capabilities.

• Identifyemerging fraud and risk threats,connectthe right stakeholders, and lead complex, cross-functional initiatives and escalations across security, compliance, legal, engineering, and customer experience to rapidly mitigate risk.

• Apply deep data analytics and machine learning insights to continuouslyoptimizefraud and risk models, safelyintegrateandoperateAI/MLenabledsolutions that improve outcomes, and foster a culture of coaching, knowledge-sharing, and inclusive collaboration across product teams.

Minimum Qualifications:

• 12+ years of relevant experience with aBachelor'sdegree, or 10+ years with aMaster'sdegree, in product leadership roles focused on fraud, payments, risk, or closely related domains or equivalent practical experience.

• Proven ownership of end-to-end performance for fraud and risk products or platforms, including accountability for metrics such as fraud loss, false positives, chargebacks, and customer friction across multiple workstreams or a suite of products.

• Demonstratedexpertisein AI/ML application to fraud detection, including anomaly detection, behavioral analytics, and pattern recognition, with familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to real world products.

• Strong fluency in data science principles, statistical reasoning, and agile practices, with the ability to translate complex technical and threat landscape considerations into clear product requirements for diverse, global stakeholders.

Preferred Qualifications:

• Deep domain knowledge spanning fraud, payments, chargebacks, dispute management, and AML/KYC fundamentals, witha track recordof shaping organization-level fraud and risk strategy in ambiguous, high-stakes environments.

• Extensive experience partnering with engineering and data science teams to architect and evolve AI/ML-enabled fraud detection and risk-scoring systems at scale, includingestablishingresponsible AI practices for model evaluation, monitoring, tuning, retraining, and bias mitigation.

• Proven ability to reverse engineer fraud patterns and adversarial behaviors,monitoremerging AI/ML and fraud trends (such as graph-based detection, behavioral biometrics, or generative-AI-enabled fraud), and translate these into innovative, scalable product capabilities.

• Demonstrated success influencing senior stakeholders beyond the immediate product area, resolving cross-workstream escalations, and coaching product managers on integrating fraud and risk considerations into customer journeys, communications, and decision-making.

• Safely integrates andoperatesAI/MLenabledsolutions that improve outcomes, with advanced experience applying AI/ML to large-scale fraud and risk environments to reduce loss while enhancing legitimate customer experience and driving sustainable business growth.