Lead Software Engineer - Java
Key Skills for This Role
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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 where your contributions shape the technology that powers one of the world's most trusted financial institutions.
Here, you'll collaborate with talented engineers, drive meaningful innovation, and grow your career in an environment that values curiosity, inclusion, and technical excellence.
As a Lead Software Engineer at JPMorganChase within the Chief Technology Office, 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
- Execute creative software solutions, design, development, and technical troubleshooting with the ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- Develop secure, high-quality production code, and review and debug code written by others
- 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 probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
- Lead communities of practice across Software Engineering to drive awareness and adoption of new and leading-edge technologies
- 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
- Foster a team culture of diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and advanced applied experience
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Advanced proficiency in one or more programming languages
- Proficiency in automation and continuous delivery methods
- Proficiency in all aspects of the Software Development Life Cycle
- Advanced understanding of agile methodologies such as continuous integration/continuous delivery, 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 its technology systems
- Practical cloud-native experience
- 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
Preferred qualifications, capabilities, and skills
- Experience with Java, Spring Boot, Spring MVC, Spring Data in a production environment
- Demonstrated ability to design and deliver microservices with high reliability, clear APIs, and strong test coverage
- Proficiency in API design principles including REST best practices, OpenAPI/Swagger, versioning, and backward compatibility
- Experience with relational databases (e.g., PostgreSQL, Oracle) and/or NoSQL databases, including indexing, transactions, and migrations
- Familiarity with observability tooling such as distributed tracing, log aggregation, and metrics platforms (e.g., OpenTelemetry, Prometheus, Grafana)
- Experience with containerization and orchestration technologies such as Docker and Kubernetes
- Experience writing unit, integration, and contract tests using testing frameworks and libraries such as JUnit, Mockito, or Testcontainers
About JPMorgan Chase
Global financial services and investment banking firm.
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