at J.P. Morgan
Bulge Bracket Investment BanksPosted 11 days ago
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**Java Lead Software Engineer in Jersey City, NJ** As a Lead Java Engineer at JPMorgan Chase's Asset & Wealth Management tech team, you'll guide an agile squad in delivering secure, scalable solutions. Key responsibilities include: - Crafting innovative software solutions and troubleshooting using Java, React, Kafka, Oracle, Aurora, Airflow, and Spark. - Driving AI-assisted engineering practices, such as AI-assisted code review and test acceleration, while ensuring security and quality standards. - Setting engineering standards, reference architectures, and guiding cloud deployments (public and private). - Automating issue resolution and leading vendor evaluations to enhance systems. Bring 5+ years of Java/Spring, cloud platforms, and AI-assisted tools experience. Preferred is knowledge of financial services IT systems. Proficient in full SDLC and agile methodologies. Hände-on experience in Java, JavaScript/TypeScript, SQL, and cloud platforms is required. Past banking or buy-side experience is desirable but not essential.
- Compensation
- Not specified
- City
- Jersey City
- Country
- United States
Currency: Not specified
Full Job Description
Location: Jersey City, NJ, United States
As a Lead Software Engineer at JPMorganChase within the Asset & Wealth Management technology 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 firms business objectives.
Job Responsibilities
- Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
- Develops secure and high-quality production code, and reviews and debugs code written by others
- 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.
- Set engineering standards and reference architectures across Java, React, Kafka, Oracle, Aurora, Airflow, and Spark. Guide deployments to both public and private cloud environments.
- Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
- Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
Required qualifications, capabilities, and skills - A. Formal training or certification on software engineering concepts and 5+ years applied experience ( NAMR/APAC India/ LATAM/ Hong Kong)
B. Formal training or certification on software engineering concepts and advanced applied experience (EMEA/LATAM-Brazil)
C. Singapore follow local country guidance - Hands-on practical experience delivering system design, application development, testing, and operational stability
- Advanced in technologies and frameworkswhether its Java/Spring, JavaScript/TypeScript, SQL, or Kafka. Youre hands-on with cloud platforms (internal or AWS) and eager to experiment with modern development stacks.
- 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
- Proficient in all aspects of the Software Development Life Cycle
- Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- In-depth knowledge of the financial services industry and their IT systems
Practical cloud native experience
- Nice to have any banking or buy-side experience (portfolio management, OMS, trade lifecycle/middle office, risk and controls) that helps translate investment intent into compliant, scalable solutions.
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
