Lead Software Engineer - Java, Spring, AWS, AI

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 - 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. - Develops secure high-quality production code, and reviews and debugs code written by others - 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 - Adds to team culture of diversity, opportunity, inclusion, and respect Required qualifications, capabilities, and skills: - Formal training or certification in Software Engineering and 5+ years applied experience - 6+ years experience years in IT with strong CS fundamentals (algorithms, data structures, operating systems, programming languages) - 5+ years experience building mission-critical enterprise applications using Java and the Spring ecosystem (Core, Boot, Cloud). - 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 - Advanced in one or more programming language(s) : J2EE , Core Java including Java 17 with annotation, enum, collections, streaming, multithreading, concurrency, regular expressions, functions. - Strong object-oriented design and common design patterns. - REST architecture; design and implementation of RESTful APIs and web services. - 3+ years experience on private cloud (PCF) or public cloud (AWS, Azure, GCP). - Hands-on practical experience delivering system design, application development, testing, and operational stability - Advanced in one or more programming language(s) Preferred qualifications, capabilities, and skills - In-depth knowledge of the financial services industry and their IT systems - Practical cloud native experience - Proficient in all aspects of the Software Development Life Cycle - Proficiency in automation and continuous delivery methods - Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security - Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)