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.
Job 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
Required qualifications, capabilities, and skills
- 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
Preferred qualifications, capabilities, and skills
- 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