Staff Backend Engineer

<h3>Company Introduction</h3> <div> <p>We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did we ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we’re collectively disrupting the multi-billion-dollar e-commerce industry from the ground up. We are one of the fastest-growing e-commerce companies that established an unparalleled reputation for being a dominant and reliable force in South Korean commerce.</p> </div> <p>We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been since our inception. We are all entrepreneurs surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day.</p> <p>Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world.</p> <p><strong>Role Overview</strong></p> <p>The Commerce Risk Detection Systems (CRDs) team focuses on seller and buyer fraud detection and prevention across Coupang’s ecosystem. The team builds large-scale, real-time systems that analyze tens of millions of commerce events daily (orders, returns, listings) to identify fraudulent behavior and patterns.</p> <p>A Staff Backend Engineer will operate as a technical leader, driving architecture, scalability, and innovation in fraud detection systems. The team is actively evolving from rule-based systems toward ML-driven and LLM-powered detection mechanisms for future scalability.</p> <p><strong>What You Will Do</strong></p> <ul> <li>Act as a technical leader translating business fraud prevention goals into scalable technical solutions and architecture</li> <li>Design and build large-scale, low-latency backend systems processing tens of millions of events per day</li> <li>Develop and optimize real-time fraud detection systems using streaming data and inference pipelines</li> <li>Collaborate across stakeholders including Product, Data Science, ML engineers, and leadership</li> <li>Drive architectural decisions for scalable fraud detection (counterfeit detection, seller fraud, risk signals)</li> <li>Evaluate and implement ML and emerging LLM-based approaches for fraud detection use cases</li> <li>Advocate engineering excellence, including system efficiency, scalability, maintainability, and fault tolerance</li> <li>Guide best practices and act as a role model for strong engineering standards across the team</li> </ul> <p><strong>Basic Qualifications</strong></p> <ul> <li>10–12 years of backend engineering experience&nbsp;</li> <li>Strong&nbsp;experience&nbsp;building&nbsp;large-scale,&nbsp;real-time&nbsp;distributed&nbsp;systems</li> <li>Hands-on&nbsp;experience&nbsp;with&nbsp;data&nbsp;streaming&nbsp;technologies&nbsp;(e.g.,&nbsp;Apache&nbsp;Flink&nbsp;or&nbsp;similar)</li> <li>Strong&nbsp;proficiency&nbsp;in&nbsp;Java-based&nbsp;backend&nbsp;development</li> <li>Experience&nbsp;designing&nbsp;and&nbsp;building&nbsp;low-latency,&nbsp;high-throughput&nbsp;systems</li> <li>Experience&nbsp;working&nbsp;with&nbsp;OLTP&nbsp;databases&nbsp;in&nbsp;production&nbsp;environments</li> <li>Experience&nbsp;building&nbsp;or&nbsp;supporting&nbsp;real-time&nbsp;inference&nbsp;systems&nbsp;(ML&nbsp;or&nbsp;rule-based)</li> <li>Familiarity&nbsp;with&nbsp;using&nbsp;GenAI/LLM&nbsp;tools&nbsp;for&nbsp;engineering&nbsp;productivity&nbsp;(e.g.,&nbsp;coding,&nbsp;debugging,&nbsp;development&nbsp;workflows)</li> <li>Strong&nbsp;knowledge&nbsp;of&nbsp;system&nbsp;design,&nbsp;scalability,&nbsp;and&nbsp;fault&nbsp;tolerance</li> <li>Strong problem-solving skills with focus on efficiency and optimal solution</li> </ul> <h3>Preferred Qualifications</h3> <ul> <li>Experience in fraud detection, risk systems, payments risk, or similar domains</li> <li>Familiarity with commerce or fintech ecosystems (e.g., payments, marketplaces)</li> <li>Experience with Apache Flink or similar streaming frameworks</li> <li>Experience with OLTP databases and backend system design</li> <li>Exposure to ML systems, feature stores, or inference pipelines</li> <li>Familiarity with leveraging GenAI tools (e.g., code generation, debugging, productivity enhancements)</li> <li>Exposure to using existing LLMs or AI assistants in engineering workflows (not model-building, but practical usage)</li> <li>Proficiency in Java-based backend development</li> </ul> <p><strong>Type of work model</strong></p> <ul> <li>Hybrid / Onsite / Remote working<br>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.</li> </ul> <p><strong>Details to consider</strong></p> <ul> <li>Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws.</li> </ul> <p><strong>Privacy Notice</strong></p> <ul> <li>Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice located below. https://privacy.coupang.com/en/l and/jobs/</li> </ul>