Lead Software Engineer - Full Stack / React

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 Corporate Sector - Infrastructure Platforms - Data and Speciality Services 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 break down technical problems Establish AI-native engineering practices with robust validation standards to ensure speed never compromises correctness Work AI-native across the software development life cycle, using AI-assisted development, code review, test generation, and incident analysis while maintaining validaton standards 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. Own the design, delivery, and operation of enterprise-scale infrastrucutre services from architecture through production Write and review production code, maintaining a hands-on apporach and setting the bar for engineering quality 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 certificaiton on software engineering concepts and 5+ years applied experience Hands-on practical experience delivering system design, application development, testing, and operational stability 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 hands on expereince engineering with production code experience in one or more programming industry-standard language(s) and framework(s) (e.g., Python, GO, Java, C++, Rust, React, Full Stack, etc.) Deep experience building and operating systems in at least one infrastructure domain (cloud, networking, compute, storage, security, or data infrastructure) Experience running production systems at scale, including on-call ownership, indcient response, and desinging for reliability and operability Understands how to lead and mentor engineers, with setting technical direction Proficiency in automation and continuous delivery methods Proficient in all aspects of the Software Development Life Cycle Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security Preferred qualifications, capabilities, and skills Experience across multiple infrastructure domains or programming languages Track record of reducing operational toil and cost through automation and better engineering Experience adopting AI-native engineering practices at team or organizational scale Prior experience in regulated or large-scale enterprise environments Experience with greenfield builds and establishing engineering culture Ability to influence engineering patterns beyond the immediate team