About this role
Java, Python Lead Software Engineering - Risk Data Platform & Strategy
Join us and shape the future of risk technology with your expertise in data engineering and software development. You will have the opportunity to push boundaries, innovate, and make a meaningful impact on our business. We value diversity, inclusion, and respect, fostering a collaborative environment where your ideas matter. Experience career growth and mobility while working with market-leading technology products. Be part of a team that thrives on creativity and continuous improvement.
As a Lead Software Engineer at JPMorgan Chase within the Data Platform & Strategy team within Corporate Risk Technology, you will design, build, and enhance advanced data engineering solutions. You will play a pivotal role in delivering secure, stable, and scalable technology products that support our business objectives. You will collaborate with agile teams, contribute to technical strategy, and drive innovation across multiple technical areas. Your work will help shape the team culture and the impact of our technology solutions.
Job Responsibilities:
- Execute creative software solutions, design, development, and technical troubleshooting to solve complex problems
- Develop secure, high-quality production code for data-intensive applications and review code written by others
- Identify opportunities to automate remediation of recurring issues and improve operational stability
- Lead evaluation sessions with external vendors, startups, and internal teams to assess architectural designs and technical credentials
- Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
- Drive communities of practice across Software Engineering to promote new and leading-edge technologies
- Foster a team culture of diversity, opportunity, inclusion, and respect
Required Qualifications, Capabilities, and Skills:
- Proficiency in Engineering & Architecture, AI/ML, with hands-on experience designing, implementing, testing, and ensuring operational stability of large-scale enterprise data