Sr Lead Software Engineer - Engineering Excellence

JPMorganChase • Columbus, OH

3d

About The Position

At JPMorganChase, the Senior Lead Software Engineer within Corporate Technology serves as a technical authority and role model for building secure, healthy applications at scale. The role drives adoption of AI-assisted engineering practices, vulnerability remediation, and application modernization through sound architectural principles and proactive technical lifecycle management. It helps shape how engineering teams design, build, and maintain software amid the growth of agentic AI and accelerating delivery expectations.

The engineer promotes enterprise-authorized AI-assisted development and automation across teams, establishes validation standards, and encourages reuse of proven patterns throughout the Software Development Life Cycle and technical lifecycle management toolchain. The role champions application health, partners with architecture and security teams to embed secure-by-design principles, and mentors engineers in application health, AI-enabled development, and technical lifecycle practices.

Requirements

• Formal training or certification in software engineering concepts and at least 5 years of applied experience.
• Expertise building and maintaining secure, production-grade applications, including vulnerability management, dependency hygiene, and technical debt reduction.
• Hands-on experience with technical lifecycle management, application modernization, deprecated component remediation, and proactive risk identification across software portfolios.
• Experience leading effective use of enterprise-authorized AI-assisted software development tools in the work environment, with the ability to set expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and security and resiliency expectations.
• Experience coaching senior engineers and leads on compliant AI usage patterns and controls.
• Proficiency in modern software engineering practices, including CI/CD pipeline automation, automated testing strategies, secure coding standards, and peer review.
• Ability to communicate complex technical concepts to engineering and non-engineering stakeholders, influence decisions, and drive alignment across cross-functional teams.

Nice To Haves

• Experience with agentic AI coding platforms such as Claude, GitHub Copilot, or equivalent enterprise-authorized tools in a production engineering environment, including responsible governance at team or program scale.
• Familiarity with application health frameworks, static analysis tools, software composition analysis, or similar vulnerability and lifecycle management platforms.
• Experience contributing to or defining engineering standards, architectural patterns, or developer experience initiatives in a large-scale technology organization.
• Exposure to cloud-native application development and infrastructure-as-code practices, with an understanding of how platform choices affect long-term application health and maintainability.
• Background coaching or mentoring engineers on secure development practices, AI-assisted workflows, or technical modernization programs.

Responsibilities

• Drive adoption and governance of enterprise-authorized AI-assisted engineering practices and agentic coding tools across teams, establishing measurable validation standards and promoting reuse of proven patterns in the SDLC toolchain.
• Champion application health standards and model how to build secure, resilient, well-architected applications from inception.
• Lead technical lifecycle management efforts, identifying and remediating aging components, deprecated dependencies, and systemic vulnerabilities.
• Partner with architecture and security teams to embed secure-by-design principles in development workflows and meet firm-wide application health and compliance expectations.
• Guide responsible use of agentic AI coding tools, including expectations for human-in-the-loop validation, output review, and secure handling of sensitive data.
• Contribute to engineering standards and toolchain automation to reduce manual work, accelerate release readiness, and improve delivery traceability and auditability.
• Mentor and coach engineers at multiple levels on application health, AI-enabled development, and technical lifecycle practices.
• Promote AI-assisted code review and refactoring, test acceleration, release readiness, and incident or root-cause analysis, supported by validation standards such as secure coding, peer review, and automated testing.
• Apply SDLC toolchain knowledge, including approved AI-assisted development and automation capabilities, to improve the value realized from automation at scale.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed