Lead Software Engineer - Java

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 Consumer & Community Banking, 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 break down technical problems Develops secure 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 Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies Required qualifications, capabilities, and skills: Formal training or certification on software engineering concepts and 5+ years applied 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 Strong hands-on experience in Java backend development and Spring Boot in production environments Proven ability in system design for scalable, secure services using microservices and API-driven architectures Strong engineering fundamentals including object-oriented programming, design patterns, concurrency, debugging, and performance tuning Solid testing discipline encompassing unit and integration testing, automation, and code quality practices Advanced proficiency in programming languages (Java, Python, C#, etc.), Hands-on work with Large Language Models (LLMs) and generative AI. Experience with distributed systems and cloud platforms (AWS, GCP, Azure). Expertise in microservices, RESTful APIs, and database technologies (relational/NoSQL) and experience with development and testing tools and frameworks (JUnit, UDF, Tophat, Cucumber , Groovy, Postman, REST Assured, Eclipse, Maven, Jenkins, IntelliJ). Experience with performance testing tools (JMeter, Blazemeter) and Chaos Monkey Testing. Preferred qualifications, capabilities, and skills: Cloud certification (AWS, GCP, Azure). Practical public cloud development experience. In-depth knowledge of the financial services industry and their IT systems. Wealth Planning tool experience Effective communication across teams and management, with a proactive approach to process improvement. Strong system design, application development, and operational stability skills. Familiarity with AI/ML frameworks (PyTorch, scikit-learn, Hugging Face).