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Lead Software Engineer
lead · Technology / Software Development
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
JPMorgan Chase offers a unique opportunity to advance your career while driving innovation at the forefront of financial technology. Join us in shaping the future of banking through cutting-edge solutions and transformative initiatives.
As a Lead Software Engineer at JPMorgan Chase within the Consumer & Community Banking - Auto Line of Business (CCB-Auto LOB), you will serve as an integral member 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 architecting and implementing critical technology solutions across multiple technical domains within various business functions, directly supporting the firm's strategic business objectives.
Job Responsibilities
- Execute creative software solutions through design, development, and technical troubleshooting, demonstrating the ability to think beyond conventional approaches to architect innovative solutions and resolve complex technical challenges
- Develop secure, high-quality production code while conducting thorough code reviews and debugging activities for code written by team members
- Proactively identify opportunities to eliminate or automate the remediation of recurring issues, thereby improving the overall operational stability and reliability of software applications and systems
- Lead technical evaluation sessions with external vendors, startups, and internal teams to conduct outcomes-oriented assessments of architectural designs, technical credentials, and applicability for integration within existing systems and information architecture
- Lead and facilitate communities of practice across Software Engineering to promote awareness, adoption, and best practices for emerging and leading-edge technologies
- Contribute to and foster a team culture that values diversity, equity, inclusion, and respect
- 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
Required Qualifications, Capabilities, and Skills
- Proven experience in architecting, building, and supporting scalable, multi-tenant distributed applications for product-based and financial services organizations
- Demonstrated experience driving large-scale technology transformation initiatives utilizing microservices architecture in both public cloud (AWS) and hybrid on-premise environments
- Hands-on expertise with AWS deployment, including the ability to identify and define technical requirements for AWS-based applications, select appropriate AWS services to meet specific technical requirements, and comprehensive understanding of network technologies and security features within the AWS ecosystem and their relationship to traditional services
- Deep technical proficiency in building, containerizing, and scaling microservices-based applications using AWS Lambda, Docker, and Kubernetes
- Excellent understanding and hands-on experience with Design Patterns, Core Java, J2EE Frameworks, Spring Boot, JPA, RESTful APIs, and Web Services
- Expert-level proficiency in Oracle or PostgreSQL databases, including advanced query optimization techniques
- Practical experience working with NoSQL databases such as MongoDB, Elasticsearch, Cassandra, and Neo4j
- Working knowledge of enterprise messaging middleware platforms such as Apache Kafka or TIBCO MQ
- 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
- Knowledge and experience with Artificial Intelligence/Machine Learning (AI/ML) and Data Warehousing technologies
- Proficiency in front-end technologies such as Angular and React
- Domain knowledge and exposure to the Banking and Financial Services industry