We have an opportunity to impact your career and provide an adventure where you can push the limits of what’s possible. Join a team that values innovation, collaboration, and continuous improvement. You’ll help build trusted technology products that support meaningful business outcomes. You’ll grow your technical leadership and influence how we design, develop, and deliver software. Our culture prioritizes inclusion, respect, and opportunity for all.
Job Summary
As a Lead Software Engineer in the EVO team, you will play a key role in enhancing, building, and delivering market-leading technology products in a secure, stable, and scalable way. You will act as a core technical contributor, conducting critical technology solutions across multiple technical areas and business functions to support the firm’s objectives. You will help set high standards for code quality, resiliency, and security through hands-on engineering and thoughtful collaboration. You will contribute to a team culture grounded in diversity, opportunity, inclusion, and respect.
Job Responsibilities
Execute creative software solutions through design, development, and technical troubleshooting to break down complex problems
Develop secure, high-quality production code and review and debug code written by others
Drive 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
Apply 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
Identify opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
Lead evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented review of architectural designs, technical credentials, and fit within existing systems and information architecture
Lead communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
Contribute to a team culture of diversity, opportunity, inclusion, and respect
Drive 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
Apply 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
Required Qualifications, Capabilities, and Skills
Hands-on practical experience delivering system design, application development, testing, and operational stability
Advanced proficiency in one or more programming languages
Expert Java Programmer (Java 11+) with dedication to clean, maintainable code
Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security
Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices
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)
Practical cloud-native experience
In-depth knowledge of software design and architecture principles
Agile SDLC experience – Scrum, code reviews, and mentoring junior team members
Experience using modern engineering toolchains for build, dependency management, CI/CD, and code quality (e.g., Git, Gradle, Jenkins, Sonar)
In-depth knowledge of the financial services industry and their IT systems
Preferred Qualifications, Capabilities, and Skills
- Strong Linux command line skills
- Cloud platform experience, preferably AWS
- Familiarity with modern web UI technologies
Job description provided by JPMorgan Chase.
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