Lead Software Engineer - Analytics & Feedback Platforms

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 JPMorgan

Chase within the 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.

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
• Develops secure and high-quality production code, and reviews and debugs code written by others
• 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.
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Leads 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

• Formal training, certification, or equivalent experience in Software Engineering with 5+ years of applied experience designing, developing, and delivering enterprise software solutions.
• Hands-on experience in system design, application development, testing, deployment, and operational support of scalable and resilient applications.
• Advanced proficiency in one or more programming languages, with demonstrated ability to develop high-quality, maintainable, and secure code.
• Demonstrated experience using AI-assisted software development tools to improve engineering efficiency, including code generation, code reviews, testing, troubleshooting, and documentation, while ensuring output quality, security, and performance standards.
• Strong understanding of Responsible AI practices within engineering workflows, including data sensitivity, secure handling of inputs and outputs, compliance with enterprise standards, and coaching team members on safe AI adoption.
• Proficient in all phases of the Software Development Life Cycle (SDLC), including requirements analysis, design, development, testing, deployment, monitoring, and support.
• Advanced understanding of Agile software development methodologies, CI/CD pipelines, application resiliency, observability, and security best practices.
• Experience developing and supporting technology solutions within the financial services industry or other highly regulated environments.
• Hands-on experience building and deploying cloud-native applications, leveraging modern cloud platforms, microservices, and distributed architectures.
• Strong server-side development experience with Java, JEE, Spring, Spring Boot, REST APIs, Kafka, JUnit, integration testing, and Behavior-Driven Development (BDD) practices.
• Proven programming and coding expertise with a passion for delivering high-quality, scalable, secure, and production-ready applications that drive business value.

• Strong analytical and problem-solving skills, with the ability to evaluate multiple solution options and make sound technical decisions with limited oversight.
• Working knowledge of financial services technology environments, controls, compliance expectations, and regulatory considerations.
• Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field, or equivalent practical experience.