Senior Staff Backend Engineer - Fraud Detection

Key Responsibilities: Lead the architecture, design, and development of scalable data and ML infrastructure supporting fraud detection, risk evaluation, and trust systems. Build and optimize large-scale batch and real-time data pipelines capable of processing high-volume events with low latency and high reliability. Own the end-to-end productionization of machine learning models, ensuring deployment architectures meet performance, scalability, and operational requirements. Partner closely with Data Scientists and Engineering teams to bridge model development and production deployment, translating complex modeling requirements into scalable engineering solutions. Define long-term technical vision and roadmap for data processing, ML platform capabilities, and fraud detection infrastructure. Lead complex cross-functional initiatives, establish engineering best practices, and raise the bar for system scalability, reliability, and operational excellence. Mentor senior engineers, drive technical decision-making, and provide leadership during critical production incidents and architectural reviews. Basic Qualifications 13+ years of experience in backend engineering, data engineering, or large-scale distributed systems development Strong experience building large-scale, real-time distributed data processing systems Hands-on experience with data streaming technologies such as Apache Flink, Kafka, Spark Streaming, or similar frameworks Strong proficiency in Java-based backend development and distributed system architecture Experience designing and building low-latency, high-throughput data pipelines and serving systems Experience deploying, scaling, and optimizing machine learning models in production environments Strong knowledge of system design, scalability, fault tolerance, and operational excellence Preferred Qualifications Experience in fraud detection, risk systems, trust & safety, payments risk, or similar domains Familiarity with commerce, marketplace, fintech, or payments ecosystems Experience building ML platforms, model-serving infrastructure, feature stores, or inference pipelines Experience operating systems that process millions of events or transactions per day Experience partnering closely with Data Science teams to productionize machine learning models Familiarity with leveraging GenAI tools for software development, debugging, testing, and engineering productivity Experience working with cloud-native architectures, containerized environments, and modern infrastructure platforms Type of work model Hybrid / Onsite / Remote working Our Hybrid work model: Coupang hybrid work model is designed to enable a culture of collaboration that acts a catalyst to enrich the experience of employees. Employees are required to work at least 3 days in the office per week, with the flexibility to work from home 2 days a week, depending on the role requirement. Some businesses may require more time in office due to nature of work. Details to consider Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws. Privacy Notice Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice located below. https://privacy.coupang.com/en/land/jobs/