Senior Lead Software Engineer - Java, SpringBoot, Microservices

JPMorganChase • Jersey City, NJ

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About The Position

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. As a Vice President at JPMorganChase within the Commercial Investment Bank, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Requirements

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Hands-on practical experience in system design, application development, testing, and operational stability
• Proficient in coding in one or more languages - Java 11+ , Modern Java. Proficiency in Java 11 and Java 21 with modern features (var, streams, records, switch expressions, Jakarta EE namespace).
• Extensive use of Spring Boot 3.x, Spring Framework 5.x,6.x with dependency injection, configuration management, and Spring ecosystem components (Spring JMS, Spring Web, Spring Kafka)
• Enterprise Messaging & Integration - Strong experience with IBM MQ (Jakarta JMS API), Apache Kafka, and message driven architectures.
• Apache Camel 4.x for enterprise integration patterns and routing, Building RESTful APIs with Spring, Apache CXF for SOAP services, understanding of HTTP clients (Apache HttpClient) and web service security
• Experience with Microsoft SQL Server, JDBC, Spring JDBC templates, stored procedures, and DAO pattern implementation
• Strong testing skills with JUnit 5 (Jupiter), Mockito for mocking, test-driven development practices, and achieving good code coverage.
• Deep understanding of Maven for dependency management, build lifecycle, multi-module projects, and plugin configuration
• Financial industry experience
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs, outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices

Nice To Haves

• AWS Cloud Services - Experience with AWS MSK (Managed Streaming for Kafka), cloud-native application deployment, and AWS infrastructure integration
• Microservices Architecture - Hands-on experience designing and implementing microservices, understanding of distributed systems, service-to-service communication, and resilience patterns
• Cucumber/BDD Testing - Behavior-driven development with Cucumber for acceptance testing, creating feature files, and maintaining living documentation

Responsibilities

• Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review, refactoring, test strategy acceleration, incident, root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
• Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident, root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
• Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
• Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
• Contributes to software engineering communities of practice and events that explore new and emerging technologies
• Adds to team culture of diversity, opportunity, inclusion, and respect

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed