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JPMorgan Chase & Co.

Lead Software Engineer - Java/Microservices/AWS

town of newark, WI

Check who can apply and the requirements below before continuing.

About this opportunity

JPMorgan Chase & Co. lists this Lead Software Engineer - Java/Microservices/AWS opportunity in town of newark, Wisconsin. Review the employer’s description below for duties, qualifications and application requirements.

Job description

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As an Lead Software Engineer - Java/Microservices/AWS at JPMorgan Chase within Commercial & Investment Bank's Post Trade Technology Reporting team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives. This group is going through a migration and modernization journey where you will be contributing to designing products, owning the design end-to-end, designing & building applications, and other technical leadership activities.

Job responsibilities

Develop code that conforms to the design, addresses non-functional requirements, and complies with the coding standards and conventions

Create detailed Unit Test cases, perform unit testing, integration testing, support QA and User acceptance testing and also address ad hoc user queries

Practice test-driven development, automated testing and continuous integration

Actively participate in peer review sessions by evaluating code quality, ensuring adherence to best practices, identifying defects, and providing constructive, actionable feedback to improve overall team deliverables

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.

Mentor and support junior developers by offering technical guidance, conducting knowledge-sharing sessions, reviewing their work, and fostering skill development to strengthen team capabilities

Analyze programs and troubleshoot production issues. Identify potential performance tuning improvement areas and implement tuning measures

Collaborate with regional and global team members from other regions

Possess a good understanding of change management and release processes

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and 5+ years applied experience

Hands-on experience coding in one or more programming languages, including Java

Experience designing and implementing applications using Spring Boot

Hands-on experience with AWS Cloud technologies

Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages

Overall knowledge of the Software Development Life Cycle

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

Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security

Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)

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