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 - AWS, Python/Java - AI/ML at JPMorgan Chase within the within the Consumer & Community Banking's Wealth Management Technology 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 • Develops secure and high-quality production code, and reviews and debugs code written by others • 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. • 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 Required qualifications, capabilities, and skills • Formal training or certification on software engineering concepts and 5+ years applied experience • Strong experience in Data Engineering , Python, SQL, AWS Tech Stack • Exposure to knowledge graphs, entity resolution, Anomaly detection, or recommendation systems . • Strong hands-on Python development experience, with the ability to design, build, and support production-grade applications and data pipelines. • Demonstrated proficiency in PySpark and AWS Glue, with the ability to build and optimize distributed data-processing workflows. • Strong SQL skills and experience working with data processing and data engineering workloads. • Hands-on experience with AWS cloud services and building cloud-native solutions. • Solid software engineering fundamentals, with experience delivering and supporting solutions in a production environment. • 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 Preferred qualifications, capabilities, and skills • Proficiency in automation and continuous delivery methods; strong SDLC discipline (CI/CD, testing, code quality, release controls) • Advanced understanding of agile delivery, application resiliency, and secure engineering practices • Strong hands-on Java development experience • Knowledge of responsible AI practices, including secure data handling, traceability, and governance in regulated environments. • Prior experience in financial services domain
Skills: aws python java ai/ml agile technical troubleshooting code quality code review automated testing software development