(USA) Staff, Software Engineer - Fraud and Risk Platform

Job Description

Position Summary... What you'll do... As a Staff Engineer in Walmart’s Fraud & Risk platform, you will build and scale intelligent systems that detect, prevent, and explain fraud across Walmart’s ecosystem. You will work on next-generation platforms spanning real-time decisioning, entity resolution, agentic AI-driven fraud analysis, and human-in-the-loop case management. This is a hands-on role focused on delivering high-quality distributed systems and integrating AI/ML capabilities into production workflows in a low-latency, high-scale environment. About Team: The Inkiru team's mission is to detect and prevent Fraud in real time and enable a safe shopping experience for all our customers online and in-store. We are a team of passionate Engineers, Data scientists and Product managers who love to challenge each other but work together to build a platform to find the proverbial needle in a haystack. As an engineer on the team, you will help build systems that can process data at the scale of Walmart to derive insights in milliseconds that power lightning-fast detection of fraudsters. You will have the opportunity to work closely with our data scientists, Product Managers, business partners and systems engineers to drive the definition and implementation of platform services, applications and analytics tools for our predictive intelligence platform. What you'll do: Build End-to-End Fraud & Risk Systems Develop platforms for real-time abuse detection (card testing, checkout fraud, signup abuse, offer exploitation) Contribute to policy engines for dynamic, runtime decisioning Build entity resolution systems to detect coordinated abuse patterns Enhance case management systems for investigator workflows Integrate AI/ML into Production Systems Work closely with Data Scientists to productionize ML models Integrate AI-driven workflows and agentic systems for fraud analysis Build systems that support decision explainability and feedback loops Own the Software Lifecycle Design, build, test, deploy, and operate services end-to-end Implement observability, monitoring, and reliability best practices Improve developer productivity through tooling and platform enhancements Collaborate Across Teams Partner with Gateway teams for real-time decision integration Work with Platform teams on shared infrastructure and services Align with Data Science teams on model integration and iteration Drive Engineering Excellence Participate in design reviews and contribute to architecture decisions Mentor engineers and promote strong engineering practices Continuously improve system scalability, performance, and maintainability What you'll bring: Strong experience building distributed systems and backend platforms at scale Proficiency in one or more: Java, Python, JavaScript/TypeScript, or similar Experience with real-time systems, event-driven architectures, and microservices Experience working with or integrating ML models into production systems Familiarity with ML concepts (c

Required Skills