Staff Software Engineer, Fraud & Payment Risk Platform
Flex · USA
About this role
**Flex — Staff Software Engineer, Fraud & Payment Risk Platform** **About the role** Flex is looking for a **Staff Software Engineer** to build and scale its **Fraud and Payment Risk Platform**. You’ll lead the architecture and hands-on development of backend services and shared infrastructure for fraud prevention and payment risk decisioning. The platform combines **real-time, near-real-time, and offline/batch-computed** risk features with **business rules, machine learning model outputs, and experimentation**. You’ll make these capabilities **reliable, scalable, and observable**, enabling teams to develop, validate, and launch risk strategies faster and more safely. This is a **hands-on backend and platform** role with technical ownership from **architecture through production**. You’ll collaborate with **product, risk policy, data science, and engineering** to turn risk strategies into reusable platform capabilities—covering feature ingestion/integration, UAT, experimentation, and infrastructure across the full **ML lifecycle** (development/validation → deployment/serving → production monitoring). **What you’ll do** - **Lead backend architecture and development** for the Fraud and Payment Risk Platform (decisioning services, APIs, shared infrastructure). - **Design for scalability, performance, and reliability**, balancing latency, throughput, availability, consistency, and cost. - **Build feature ingestion, integration, and serving** for real-time, near-real-time, and offline/batch features (freshness, correctness, availability). - **Develop infrastructure for rules and experimentation** (configure/version strategies, run UAT, evaluate changes, safe rollouts). - **Own engineering infrastructure across the ML lifecycle** (workflows, deployment, inference, versioning, safe rollouts/rollback, integration of model outputs). - **Own monitoring and alerting** across the platform (service health, feature freshness/quality, rule/experiment execution, model inference). Partner with risk policy + data science on model behavior and decision outcomes. - **Improve platform extensibility and usability** so teams can add features/rules/models/experiments without duplicating infrastructure or tightly coupling systems. - **Drive complex initiatives** from design through production (design proposals, implementation, performance testing, migration planning, cross-team coordination). - **Raise the engineering bar** via design/code reviews, mentorship, and improvements to testing, documentation, deployment safety, and operations. **Backend stack** - **Java, Spring Boot, Python, AWS** **Qualifications** **Minimum qualifications** - **6+ years** professional software engineering experience building and operating backend systems in production. - **5+ years** hands-on **Java** experience, including **Spring Boot**. - Experience leading architecture and delivery of complex distributed systems or shared backend platforms. - Strong understanding of **API design, service integration, data modeling, caching**, and distributed-system failure modes. - Experience diagnosing performance bottlenecks and improving scalability/reliability via measurement, testing, and production troubleshooting. - Experience with cloud infrastructure, containerized deployments, and relational + NoSQL data stores. - Experience establishing **observability, monitoring, and alerting** for production systems. - Ability to lead technical decisions across teams, communicate trade-offs
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