Lead Software Engineer - Java/Microservices/AWS/AI

JPMorgan Chase & Co.; Wilmington (DE); On-site; USD 150,000 - 190,000; Full time

Job summary

JPMorgan Chase & Co. is seeking a Lead Software Engineer - Java/Microservices/AWS/AI to join the Digital Utilities team. You will serve as a core technical contributor across multiple domains, delivering trusted, scalable technology products in a secure environment.

You will lead AI-assisted development practices, mentor engineers, and collaborate with vendor and internal teams to drive architecture decisions while maintaining strong security and resiliency standards.

Qualifications

• 5+ years of hands-on software development experience.
• Proficient in Java, Spring Boot, microservices, APIs, Kafka, Cassandra, AWS, and AI.
• Experience leading AI-assisted software development practices.
• Strong understanding of secure coding and SDLC.
• Knowledge of agile methodologies including CI/CD and security.

Responsibilities

• Executes creative software solutions, design, development, and troubleshooting with ability to go beyond routine approaches.
• Develops secure, high-quality production code and reviews code written by others.
• Leads AI-assisted engineering practices to improve code quality, delivery speed, and operations, with validated AI outputs.

Skills

Java

Spring Boot

Microservices

APIs

Kafka

Cassandra

AWS

AI

Tools

CI/CD tooling

AI-assisted dev tools

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 - Java/Microservices/AWS/AI at JPMorganChase within the Digital Utilities 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.

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.
• 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

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Advanced in one or more programming language(s) including Java, Springboot, Microservices, API, Kafka, Cassandra, AWS and AI
• 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

Preferred qualifications, capabilities, and skills

• Emerging technologies