Lead Fraud Technology Engineer - AI & Decision Systems (Remote)
Home Depot
Join The Home Depot’s mission to protect our customers and business by leading the charge in enterprise fraud prevention. This role drives innovation in fraud detection through AI, real-time analytics, and hands-on tech leadership.
Key Responsibilities:
Own and manage the enterprise fraud technology stack end-to-end, ensuring robust, scalable, and real-time defenses.Design and implement AI-driven decisioning systems to detect and prevent fraud across all channels.Integrate best-in-class fraud prevention platforms and tools into the enterprise ecosystem.Set technical strategy and guide architectural decisions to support long-term fraud mitigation goals.Collaborate cross-functionally with fraud analysts, investigators, data scientists, and engineering teams to stay ahead of emerging threats.Lead the development of real-time fraud detection capabilities using advanced analytics and machine learning.Maintain hands-on involvement in coding, system design, and platform optimization.Monitor fraud trends and continuously evolve technology solutions to address new attack vectors.Ensure high availability, performance, and reliability of fraud detection systems in production environments.Champion innovation and experimentation in fraud prevention technologies and methodologies.Provide technical leadership and mentorship to junior engineers and cross-functional partners.
Preferred Experience & Skills:
Hands-on experience integrating and implementing fraud prevention platforms such as ThreatMetrix, Ekata, Forter, Kount, or similar.Architectural fluency in data pipelines (Kafka, Spark, ETL frameworks), APIs, and microservices for fraud signal ingestion and scoring.Experience with cloud platforms (AWS, GCP, or Azure) and microservices architecture.Strong knowledge of data structures, AI/ML implementation, and real-time data processing.Proven track record building and operationalizing real-time scoring pipelines for Account Takeover (ATO) and Account Origination (AO) fraud.Expertise in designing scalable fraud decision engines and rule orchestration layers.Strong background in digital fraud mitigation techniques—including device fingerprinting, IP reputation, velocity/rule checks, and anomaly detection—ideally in an e-commerce or retail context.
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