JPMorgan Chase
From JPMorgan Chase's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
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.
Experience developing, debugging, and maintaining code in a large enterprise environment using modern programming languages and database query languages.
Proficiency in multiple modern programming languages, with demonstrated depth in at least one.
Demonstrated experience building distributed applications in Java 8+, including RESTful APIs, microservices, and Spring Boot.
Experience delivering multi-threaded, high-throughput, mission-critical systems with performance and latency considerations.
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.
Experience with cloud-native application development (e.g., GCP or private cloud).
Experience deploying and supporting applications on AWS.
Experience with messaging technologies such as Kafka or IBM MQ.
Experience with database platforms such as Cassandra, Oracle, Aurora, or DynamoDB.
Experience with behavior-driven development tools such as Cucumber.
Experience configuring and operating continuous integration pipelines such as Jenkins.
Proficiency with Python and Linux shell scripting.
Experience building open-source libraries or internal shared libraries adopted by multiple engineering teams.
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