Fraud Tech Lead Software Engineer - Cloud
Explicitly calls for vibe coding experience and use of AI-assisted developer tools like GitHub Copilot and AI agents for engineering productivity.
About the Role
Lead a fraud protection engineering team to design, build, and operate scalable, secure cloud-based payment fraud solutions, driving performance, reliability, and adoption of enterprise AI-assisted development practices. The role focuses on hands-on Java/Spring microservices development, system design, performance optimization, and influencing cross-functional stakeholders.
Job Description
Role
Lead Software Engineer within the Payments Trust and Safety Technology group focusing on Fraud Protection. Build cloud-native solutions for merchants to detect and prevent fraudulent behavior while ensuring performance, scalability, security, and operational stability.
Key Responsibilities
- Design, develop, review, and troubleshoot secure, high-quality production code.
- Monitor and analyze product performance and scalability across environments.
- Serve as a performance advisor, integrating performance considerations into development practices and optimizing infrastructure scalability.
- Influence leaders and senior stakeholders across business, product, and technology teams.
- Anticipate and mitigate performance and reliability issues; define standard performance benchmarks.
- Design and implement automation and tooling for performance measurement and analysis.
- Drive team adoption of enterprise-authorized AI-assisted engineering practices (code review/refactoring, test acceleration, incident analysis) while establishing validation standards (secure coding, peer review, automated testing).
Requirements
- Formal training or certification in Software Engineering and 5+ years of applied experience.
- Hands-on experience with system design, application development, testing, and ensuring operational stability.
- Advanced development experience in Java, Spring Boot, and microservices.
- Experience with AWS services such as ECS/EKS, Lambda, S3, EC2, Kafka, and NLB.
- Experience with databases and SDLC toolchains, including CI/CD, application resiliency, and security practices.
- Demonstrated experience leading use of approved AI-assisted development tools and coaching engineers on safe, compliant adoption.
- Strong understanding of responsible AI use, data sensitivity, and secure handling of AI inputs/outputs.
- In-depth knowledge of financial services industry IT systems.
Preferred Qualifications
- Enterprise architecture design experience enabling unified UX and data sharing (APIs, Kafka).
- Experience with case management workflows and orchestration across cross-functional teams.
- Vibe coding experience and familiarity with developer assistant tools like GitHub Copilot.
Team Context
Role sits within J.P. Morgan’s Commercial & Investment Bank payments and trust & safety organization, working on global banking and payments technology solutions.