Walmart is looking to solve the problem of scaling fraud detection systems by defining and leading the architecture for fraud detection infrastructure across APIs, backend systems, and platform components.
Requirements
- Expertise in building large-scale, distributed backend systems and APIs.
- Strong understanding of real-time data processing, model inference pipelines, and infrastructure at scale.
- Proven success designing internal tooling for analyst, operations, or data science use cases.
- Experience driving architectural transformation across both application-level and platform-level domains.
- Deep knowledge of modern ML platforms, cloud-native services, and enterprise-grade system reliability.
- Prior experience in fraud, risk, or identity domains is preferred
- Master’s degree in computer science, computer engineering, computer information systems, software engineering, or related area and 4 years' experience in software engineering or related area
Responsibilities
- Define and lead the architecture for fraud detection infrastructure across APIs, backend systems, and platform components.
- Design end-to-end technical solutions for fraud surfaces including Sign-in, Sign-up, Returns, Payment Risk, Driver and Seller Risk.
- Own architectural evolution for shared services like the Gateway Layers, Customer Identity Graph, Device Fingerprinting, and Risk APIs.
- Partner with platform teams to modernize key components such as databases, feature stores, and streaming/batch pipelines.
- Lead development and scaling of critical internal tools
- Drive enhancements in Rules Engines ,Workflow Engines to support hybrid decision logic (rule + ML stack).
- Champion ML Ops and model lifecycle tooling to support training, deployment, monitoring, and governance at scale.
Other
- Work closely with cross-functional pods to ensure timely and technically sound delivery of fraud solutions.
- Collaborate with QA and Release Engineering to strengthen production readiness, monitoring, and holiday resilience.
- Ensure architectural alignment and technical consistency across fraud initiatives globally.
- Mentor senior engineers and guide junior team members in technical and architectural decisions.
- Lead cross-org technical reviews and serve as a go-to expert on distributed systems and fraud infra.
