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About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
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As a Senior Lead Software Engineer within Corporate Technology, you will serve as a technical authority focused on engineering excellence. You will drive the adoption of enterprise-authorized AI-assisted engineering practices, including agentic coding tools like Claude and GitHub Copilot, to improve code quality and delivery speed. Your daily responsibilities include championing application health standards, managing technical lifecycles by remediating deprecated dependencies and vulnerabilities, and embedding secure-by-design principles into development workflows. You will mentor engineers on AI-enabled development while ensuring human-in-the-loop validation for automated outputs. The role requires expertise in CI/CD pipeline automation, automated testing, and software composition analysis to manage large-scale application health. You will solve complex problems regarding technical debt reduction and the responsible integration of agentic AI tools within a secure, high-scale production environment.
Drive the adoption and governance of enterprise-authorized AI-assisted engineering tools to improve code quality and delivery speed.
Establish measurable validation standards for human-in-the-loop review and secure handling of data within AI-assisted workflows.
Champion application health by ensuring new software is built in a secure, resilient, and well-architected state.
Lead technical lifecycle management to identify and remediate aging components, deprecated dependencies, and systemic vulnerabilities.
Embed secure-by-design principles into development workflows in partnership with architecture and security teams.
Automate engineering toolchains to reduce manual toil and improve traceability across the delivery pipeline.
Mentor and coach engineers on application health, AI-enabled development, and technical lifecycle practices.
What we're looking for
Formal training or certification on software engineering concepts and 5+ years of applied experience.
Expertise in building and maintaining secure, production-grade applications with a focus on vulnerability management and technical debt reduction.
Hands-on experience with technical lifecycle management practices, including application modernization and proactive risk identification.
Experience leading the use of enterprise-authorized AI-assisted software development tools while ensuring output validation for security and performance.
Strong understanding of responsible AI usage in engineering workflows, including data sensitivity and compliant usage patterns.
Proficiency in modern software engineering practices, including CI/CD automation, automated testing, and secure coding standards.
Ability to communicate complex technical concepts to both engineering and non-engineering stakeholders to drive alignment.
Experience with agentic AI platforms, application health frameworks, or cloud-native development (preferred).