✨ AI Summary
As a Lead Software Engineer at JPMorgan Chase within the Consumer and Community Bank, you will be an integral part of an agile team enhancing, building, and delivering technology products. You will execute creative software solutions, design, develop, and troubleshoot technical issues, and drive team adoption of enterprise-authorized AI-assisted engineering practices. You will also apply knowledge of the Software Development Life Cycle toolchain, identify opportunities to automate remediation of recurring issues, and lead evaluation sessions with external vendors and internal teams.
Required qualifications include formal training or certification on software engineering concepts and 5+ years of applied experience, with hands-on practical experience in system design, application development, testing, and operational stability. You will lead the design and delivery of Java/Spring Boot microservices, defining service boundaries, APIs (REST), data models, and integration patterns. Production-grade engineering skills including performance tuning, resilience, observability, and incident/root-cause management are essential. Experience driving cloud-native delivery on AWS with CI/CD, containerization, and automated testing, alongside providing technical leadership through code reviews, architectural guidance, mentoring, and setting engineering standards, is also required. Demonstrated experience leading effective use of AI-assisted software development tools and a strong understanding of responsible AI use are crucial.
🎁 Benefits & Perks
comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching
Requirements
Requires formal training or certification on software engineering concepts and 5+ years of applied experience. Must have hands-on experience in system design, application development, testing, and operational stability. Needs to lead design and delivery of Java/Spring Boot microservices, define service boundaries, APIs (REST), data models, and integration patterns. Must own production-grade engineering including performance tuning, resilience, observability, and incident/root-cause management. Experience driving cloud-native delivery on AWS with CI/CD, containerization, and automated testing is essential, along with providing technical leadership through code reviews, architectural guidance, mentoring, and setting engineering standards. Demonstrated experience leading effective use of AI-assisted software development tools and a strong understanding of responsible AI use in engineering workflows are also required.
Description
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 JPMorganChase within the Consumer and Community Bank, 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.
Job responsibilities
- Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
- Develops secure and 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
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
- Lead design and delivery of Java/Spring Boot microservices, defining service boundaries, APIs (REST), data models, and integration patterns aligned to domain-driven design.
- Own production-grade engineering: performance tuning, resilience (timeouts/retries/circuit breakers/idempotency), observability (logs/metrics/traces), and incident/root-cause management with measurable SLOs.
- Drive cloud-native delivery primarily on AWS with CI/CD, containerization, and automated testing (unit/integration/contract), ensuring secure-by-default practices (OAuth2/OIDC, secrets, OWASP).
- Provide technical leadership to the team: code reviews, architectural guidance, mentoring, and setting engineering standards (clean code, patterns, quality gates).
- 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
Preferred qualifications, capabilities, and skills
- In-depth knowledge of the financial services industry and their IT systems
- Practical cloud native experience