Staff Platform Engineer, Fraud & Payment Risk

Flex; United States; Hybrid; USD 200,000 - 250,000; Full time

Job summary

Flex is seeking a Staff Software Engineer to build and scale our Fraud and Payment Risk Platform. You will lead architecture and hands-on development of backend services and shared infrastructure for fraud prevention and risk decisioning, collaborating with product, risk policy, data science, and engineering teams.

The role covers real-time and offline features, ML lifecycle support, and production-grade infrastructure.

Qualifications

• 6+ years of professional software engineering experience, including substantial experience building and operating backend systems in production.
• 5+ years of hands-on Java experience, including building services with Spring Boot.
• Experience leading the 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 and reliability through measurement, testing, and production troubleshooting.
• Experience with cloud infrastructure, containerized deployments, and relational and NoSQL data stores.
• Experience establishing observability, monitoring, and alerting for production systems.
• Ability to lead technical decisions across teams, communicate architectural trade-offs clearly, and mentor other engineers.

Responsibilities

• Lead backend architecture and development for the Fraud and Payment Risk Platform, including decisioning services, APIs, and shared infrastructure for evolving business needs.
• Design for scalability, performance, and reliability, balancing latency, throughput, availability, data consistency, and cost.
• Build capabilities for feature ingestion, integration, and serving, supporting real-time, near-real-time, and offline/batch-computed features with attention to freshness, correctness, and availability.
• Develop infrastructure for rules and experimentation, enabling teams to configure and version risk strategies, perform user acceptance testing (UAT), evaluate changes, and safely roll them out.
• Own engineering infrastructure across the ML lifecycle, supporting development and validation workflows, deployment, inference, versioning, safe rollouts, rollback, and integration of model outputs into risk decisions.
• Own monitoring and alerting across the platform, covering service health, feature freshness and quality, rule and experiment execution, and model inference. Partner with risk policy and data science teams to monitor model behavior and decision outcomes.
• Improve platform extensibility and usability, so teams can add features, rules, models, and experiments without duplicating infrastructure or tightly coupling systems.
• Drive complex initiatives from design through production, including technical design proposals, hands-on implementation, performance testing, migration planning, and cross-team coordination.
• Raise the engineering bar through design and code reviews, mentorship, and improvements to testing, documentation, deployment safety, and operations.

Skills

Java

Spring Boot

Distributed systems

API design

Cloud

Observability

Mentorship

Leadership

AWS

Tools

AWS

Job description

Flex is seeking a Staff Software Engineer to build and scale our Fraud and Payment Risk Platform. You will lead architecture and hands-on development of backend services and shared infrastructure for fraud prevention and risk decisioning, collaborating with product, risk policy, data science, and engineering teams.

The role covers real-time and offline features, ML lifecycle support, and production-grade infrastructure.