Lead Software Engineer – AI-Native Component Engineering

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 Chief Technology Office, 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. - Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems. - 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. - Builds components to be drop-in and AI-native with automated upgrades so adopters across the enterprise stay current with minimal effort. - Leads communities of practice across Software Engineering to drive awareness and adoption of leading-edge technologies and shared frameworks. - Adds to team culture of diversity, opportunity, inclusion, and respect. 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. - Hands-on practical experience delivering system design, application development, testing, and operational stability. - Advanced skills in Java, JavaScript, or Python. - 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. - Demonstrated proficiency in a technical discipline such as cloud, artificial intelligence, or machine learning. - Practical cloud-native experience. Preferred qualifications, capabilities, and skills - Experience building SDKs, frameworks, or developer platforms that other engineering teams consume. - Experience with AI-native tooling and AI-assisted development workflows. - Demonstrated code shipped to production that leverages AI or builds AI capabilities.