As a Lead Software Engineer at JPMorganChase within the Corporate Sector - Infrastructure Platforms - Data and Speciality Services team, youare 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 firm27s 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

• 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