Sr Lead Software Engineer – Java/AWS
Design and build distributed Java/Spring Boot applications for JPMorgan Chase's Consumer & Community Banking division, lead AI-assisted engineering practices adoption, and improve system reliability through CI/CD and secure-by-design practices.
- Compensation
- Not disclosed
- Location
- New York, NY, United States
- Work setup
- Not specified
- Seniority
- Lead
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Software engineering
- Posted
Skills
Must have
- 5+ years application development experience
- System design, development, testing, and production stability experience
- Enterprise environment coding with modern languages and database query languages
- Proficiency in multiple modern programming languages with depth in at least one
- Distributed applications in Java 8+, RESTful APIs, microservices, and Spring Boot
- Multi-threaded, high-throughput, mission-critical systems with performance considerations
- Leading effective use of AI-assisted software development tools
- Responsible AI use in engineering workflows including data sensitivity and security
- Cloud-native application development (GCP or private cloud)
Nice to have
- AWS deployment and support experience
- Messaging technologies such as Kafka or IBM MQ
- Database platforms such as Cassandra, Oracle, Aurora, or DynamoDB
- Behavior-driven development tools such as Cucumber
- Continuous integration pipelines such as Jenkins
- Python and Linux shell scripting
- Building open-source or internal shared libraries adopted by multiple teams
Full description
Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.
As a Sr Lead Software Engineer at JPMorgan Chase within the Consumer & Community Banking, 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. Drive significant business impact through your capabilities and contributions and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.
Job responsibilities
- Designs software solutions, including complex debugging and technical troubleshooting, using strong problem-solving and engineering judgment.
- 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.
- Creates architecture and design artifacts for complex applications and ensure implementations adhere to defined design constraints.
- Analyzes large, diverse datasets and produce visualizations and reporting that drive continuous improvement of systems and applications.
- Identifies hidden problems and data patterns to improve coding hygiene, observability, and system architecture.
- Improves service reliability through automated testing, CI/CD, resiliency patterns, and secure-by-design engineering practices.
- Develops reusable services and shared components that enable consistency, scalability, and faster delivery across teams.
- Evaluates and adopts emerging technologies through communities of practice to deliver measurable engineering and business value.
- Collaborates within agile teams to deliver outcomes with clear technical ownership and delivery accountability.
Required qualifications, capabilities, and skills
- 5+ years of application development experience delivering production-grade software.
- Hands-on experience with system design, application development, testing, and operational stability in production environments.