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JM
JP Morgan Chase Company
Vice President Lead Java Software Engineer
Career Insights for Java Developer / Engineer
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What they do
A Java Developer or Engineer designs or improves computer software using the JAVA computer programming language. Oversees the JAVA software application development process. Analyzes customer or user needs, designs programs, writes code or instructs computer programmers, tests design, and documents programs. May assist with upgrades or maintenance.
$118,018 / year median in New Jersey
-7% projected decline
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 a Lead Software Engineer at JPMorganChase within the Asset & Wealth Management, Alternatives 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. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications. You will be a hands-on Java/Spring Boot Developer building and modernizing platforms that support alternative investments and the teams that service them. You will help re-platform critical applications from on‑premises to AWS, delivering cloud-native services with strong engineering discipline across system design, development, testing, and operational stability. You will shape distributed integration patterns, including messaging and event streaming, to improve resiliency, scalability, and observability. You will also lead effective use of enterprise-authorized AI-assisted development tools, setting team expectations for validating AI outputs for correctness, performance, and security. Job Responsibilities Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors Develops secure and high-quality production code, and reviews and debugs code written by others Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the