Lead Software Engineer - Java, AI, and Automation

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 Commercial & Investment Bank - Payments 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 - The role will involve quality and test advocacy and the individual will need to have hands on Quality Engineering and test automation experience. - Stay current with advancements in AI, test automation, and quality engineering, and proactively introduce innovative tools and practices to the team. - 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. - High level of flexibility and ability to react quickly to changing business needs in a fast-paced environment driven by market pressures. - The position will be accountable for large projects of high complexity, high risk and high visibility. - Integrate automated tests into CI/CD pipelines to enable rapid, reliable, and repeatable validation of new features and bug fixes. Required qualifications, capabilities, and skills - Formal training or certification on software engineering concepts and 7+ years hands on Software Development Life Cycle experience - Advanced level experience with building and maintaining testing automation frameworks with strong problem solving skills - Hands-on practical experience delivering system design, application development, testing, and operational stability - Advanced in one or more programming language(s), such as Java - Proficiency in automation and continuous delivery methods - Hands-on building/maintaining automation frameworks at scale - Proficient in all aspects of the Software Development Life Cycle - 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; - 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.) Preferred qualifications, capabilities, and skills - Hands on experience and knowledge of financial services industry and their technology infrastructure. - Hands on experience with Golang or RUST - Automated failure triage patterns: failure clustering, flaky test detection, rerun rules, quarantining workflows - Contract testing concepts and tools - Component/service validation patterns - Building a reliable canary testing framework