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Description: 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 JPMorgan Chase within the Infrastructure Platforms 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 breakdown technical problems - Build and operate cloud-native solutions using Kubernetes with strong systems fundamentals, on at least one cloud provider (AWS / GCP / Azure) - Develop services primarily in Golang and/or Java (either or both) - Produce secure, high-quality production code aligned to engineering best practices - Review and debug code written by others while enforcing consistent validation standards (secure coding, peer review, automated testing) - Drive consistent validation practices across the team to improve overall code quality and delivery outcomes - Promote reuse of effective patterns and scalable approaches across the team to improve engineering efficiency - Identify and implement opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability, and lead evaluation sessions with external vendors/startups and internal teams to assess architectural designs and technical fit within existing systems and information architecture - 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 - 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. Required qualifications, capabilities, and skills - Formal training or certification on software engineering concepts and 5+ years applied experience - Hands-on practical experience delivering system design, application development, testing, and operational stability - Advanced in one or more programming language(s) - 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 - Proficient in all aspects of the Software Development Life Cycle - Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security - In-depth knowledge of the financial services industry and their IT systems - Practical cloud native experience Preferred qualifications, capabilities, and skills - Spec Drive Development (SDD) experience is a plus - Strong AI tool usage fluency (comfortable leveraging AI tools in day-to-day engineering workflows) - Prior understanding of Cloud Governance is a plus