Senior Lead Software Engineer – Infrastructure Platforms

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As a Senior Lead Software Engineer at JPMorgan Chase within the Core Foundational Platforms 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.

Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems Develops secure high-quality production code, and reviews and debugs code written by others Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems Sets strategy and operating standards for agentic AI-enabled engineering across a portfolio (using enterprise-authorized tools within the work environment) to drive measurable improvements in delivery speed, reliability, and code quality (e.g., AI-orchestrated SDLC/TLM automation, release readiness gating, incident triage/root-cause acceleration, and large-scale refactoring/test modernization), while defining guardrails for validation, security, resiliency, and reuse across teams and functions. 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 at scale. 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 Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies 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. Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and 7+ years applied experience Hands-on practical experience delivering system design, application development, testing, and operational stability Advanced in one or more programming language(s) ideally including one of Go, Python, Java. Proficiency in Terraform, Ansible or other automation and continuous delivery methods. Proficient in all aspects of the Software Development Life Cycle 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.) In-depth knowledge of the financial services industry and their IT systems Demonstrated experience designing and scaling agentic AI-enabled development patterns (using enterprise-authorized tools within the work environment) across teams/functions, including establishing governance for human-in-the-loop validation, traceability/auditability, and secure handling of sensitive inputs/outputs. Strong