About the role
structured by ORIEnhance, build, and deliver trusted market-leading technology products within the Corporate Technology organization 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 at JPMorgan Chase within the Corporate Technology…
What you will do
- 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
- 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 establish
- 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
What they are looking for
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Advanced coding in Python and Java with strong grasp of design patterns, Spring/Spring Boot , and Kubernetes (k8s).
- 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
- Hands-on experience building and testing Spring Boot services and React applications, including automated unit/integration/E2E and performance testing (e.g., Cypress, JMeter , or similar tools).
- Experience leading effective use of approved AI-assisted dev tools, setting expectations for validating AI outputs (correctness, performance, security).
- Strong understanding of responsible AI use (data sensitivity, secure handling, resiliency/security expectations) and coaching engineers on compliant adoption.
- Cloud-native experience (e.g., AWS) and proficiency with automation, CI/CD, SDLC, agile, resiliency, and security practices.
Nice to have
- In-depth knowledge of the financial services industry and its IT systems
Full posting text
Enhance, build, and deliver trusted market-leading technology products within the Corporate Technology organization
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 at JPMorgan Chase within the Corporate Technology organization, you are an integral part of an agile team dedicated to enhancing, building, and delivering trusted, market-leading technology products in a secure, stable, and scalable manner. As a core technical contributor, you will be responsible for implementing critical technology solutions across multiple technical domains, supporting various business functions to achieve 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 break down technical problems Develops secure 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 Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies Adds to team culture of diversity, opportunity, inclusion, and respect Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and 5+ years applied experience Hands-on practical experience delivering system design, application development, testing, and operational stability Advanced coding in Python and Java with strong grasp of design patterns, Spring/Spring Boot , and Kubernetes (k8s). 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 Hands-on experience building and testing Spring Boot services and React applications, including automated unit/integration/E2E and performance testing (e.g., Cypress, JMeter , or similar tools). Experience leading effective use of approved AI-assisted dev tools, setting expectations for validating AI outputs (correctness, performance, security). Strong understanding of responsible AI use (data sensitivity, secure handling, resiliency/security expectations) and coaching engineers on compliant adoption. Cloud-native experience (e.g., AWS) and proficiency with automation, CI/CD, SDLC, agile, resiliency, and security practices. Preferred qualifications, capabilities, and skills In-depth knowledge of the financial services industry and its IT systems