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).