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Lead Software Engineer- Backend
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.
As a Lead Software Engineer at JPMorganChase within Employee Platforms, 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.
Working within the Mobile Appstore and Mobile Kit teams, you will help develop and maintain backend microservices that provide company-wide access and support functionality for mobile application deployments and feature sets. You will play a central role in supporting and provisioning all mobile development teams across the company.
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 and high-quality production code; review and debug code written by others.
Drive team adoption of enterprise-authorized AI-assisted engineering practices 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 (SDLC) toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
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.
Required Qualifications, Capabilities, and Skills
- Formal training or certification in software engineering concepts with advanced applied experience.
- Demonstrate hands-on experience delivering system design, application development, testing, and operational stability.
- Advance your skills in one or more programming languages, including Java, Spring Boot, AWS, ReactJS, Docker, Splunk, Junit, and IT Test.
- Lead effective use of approved AI-assisted software development tools for coding, code review, test acceleration, and troubleshooting, setting team expectations for validating AI outputs for correctness, performance, and security.
- Apply a strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs/outputs, and adherence to resiliency and security standards; coach engineers on safe, compliant adoption.
- Be proficient in all aspects of the Software Development Life Cycle (SDLC).
- Possess advanced understanding of agile methodologies such as CI/CD, application resiliency, and security.
- Bring in-depth knowledge of the financial services industry and their IT systems.
- Demonstrate practical cloud-native experience.
- Build and maintain robust automated testing practices, including unit, integration, and end-to-end testing (e.g., JUnit for Java stacks), ensuring test automation is embedded into CI/CD pipelines.
Operate and enhance production services using observability tooling (e.g., Splunk) for monitoring, incident response, root-cause analysis, and problem management; eliminate toil via automation
Preferred Qualifications, Capabilities, and Skills
Hands-on experience in full-stack software engineering delivering large-scale, production-grade systems (including design, development, testing, and operational stability).
MS or Computer Science Degree
AWS certification preferred (e.g., Solutions Architect / Developer / DevOps Engineer).
Strong experience with Docker and Kubernetes in production (containerization, deployments, rollout strategies, troubleshooting, runtime performance).
Strong automated testing expertise including JUnit and integration testing, plus CI/CD quality gates and test strategy ownership.