Writes automated unit, integration, and end-to-end tests and contributes to CI/CD pipelines with static analysis and code quality gates to deliver safe, frequent releases
Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
Supports production stability through monitoring, troubleshooting, and root-cause analysis of payment flows in containerized, Kubernetes-based environments
Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness
Analyzes production telemetry and operational data to proactively identify hidden problems and patterns, and uses these insights to drive improvements to coding hygiene and system architecture
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 5+ years applied experience
Hands-on practical experience delivering system design, application development, testing, and operational stability
Hands-on programming experience with Java, Spring Boot, and microservices architecture
Experience designing and building RESTful APIs, including API security, authentication/authorization, and API documentation
Experience with event-driven and messaging platforms such as Kafka or IBM MQ
Experience with relational databases (e.g., Oracle) and NoSQL data stores, including SQL and database schema change management
Experience with automated testing (TDD, JUnit, Mockito, BDD/Cucumber) and CI/CD pipelines (e.g., Maven, Jenkins)
Experience deploying and operating services using Docker and Kubernetes
Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security
Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices
Solid understanding of agile practices, application resiliency, and security
Preferred qualifications, capabilities, and skills
Exposure to payments or financial services technology (e.g., payment processing, clearing and settlement, fraud or sanctions screening)
Experience with event sourcing, state machine–based workflows, or high-throughput transaction processing
Experience with gRPC and Protobuf
Experience with Python for automation, internal tooling, or data analysis and reporting
Experience with observability tooling (e.g., OpenTelemetry, Grafana)
Familiarity with modern front-end technologies (e.g., JavaScript, HTML/CSS)
- Federal Deposit Insurance Act
- This position is subject to Section 19 of the Federal Deposit Insurance Act. As such, an employment offer for this position is contingent on JPMorganChase’s review of criminal conviction history, including pretrial diversions or program entries.
