Lead Software Engineer - Sr. Java/AWS Developer

Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction.

JPMorganChase 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 JPMorganChase within Consumer & Community Banking, Auto, you will be a core technical contributor on a team that builds secure, stable, and scalable technology products. You will architect and deliver critical solutions across multiple domains, partnering closely with product and engineering stakeholders to advance key business outcomes.

Job Responsibilities

• Design and deliver creative software solutions through hands-on development and technical troubleshooting, solving complex problems with durable, scalable architectures
• Build secure, high-quality production code and strengthen engineering standards through thorough code reviews, debugging, and continuous improvement of development practices
• Improve resilience and operational excellence by identifying recurring issues and automating remediation to reduce incidents and manual toil
• Lead outcomes-focused technical evaluations with external vendors, startups, and internal teams to assess solution fit, architecture quality, and integration readiness
• Promote modern engineering practices by leading communities of practice and sharing reusable patterns that improve delivery speed and consistency across teams
• Foster an inclusive, collaborative team culture that values respect, learning, and shared ownership
• 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

• Experience architecting, building, and supporting scalable, distributed applications in product-based and/or financial services environments
• Experience leading large-scale modernization initiatives using microservices architecture across public cloud (Amazon Web Services) and hybrid environments
• Hands-on experience designing and deploying Amazon Web Services solutions, including service selection, network fundamentals, and cloud security controls
• Strong experience building, containerizing, and scaling microservices-based applications using AWS Lambda, Docker, and Kubernetes
• Advanced proficiency in Java, Java Enterprise Edition (J2EE) frameworks, Spring Boot, Java Persistence API (JPA), and application integration using RESTful APIs and web services
• Strong database experience with Oracle and/or PostgreSQL, including performance tuning and query optimization
• Experience working with one or more NoSQL technologies such as MongoDB, Elasticsearch, Cassandra, or Neo4j
• Experience with messaging/event streaming 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

• Experience delivering production use cases involving artificial intelligence and machine learning (AI/ML)
• Experience with data warehousing and analytics technologies
• Proficiency with modern front-end frameworks such as Angular and React
• Domain knowledge within banking and financial services, including consumer lending and/or auto finance