As a Lead Software Engineer at JPMorganChase within the Consumer & Community Banking, youare 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 firm27s business objectives.

Job responsibilities:

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Develops secure 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

• Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies

Required qualifications, capabilities, and skills:

• Formal training or certification on software engineering concepts and 5+ years applied experience
• 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
• Advanced proficiency in programming languages (Java, Python, C#, etc.)
• Hands-on work with Large Language Models (LLMs) and generative AI.
• Familiarity with AI/ML frameworks (TensorFlow, PyTorch, scikit-learn, Hugging Face).
• Experience with distributed systems and cloud platforms (AWS, GCP, Azure).
• Expertise in microservices, RESTful APIs, and database technologies (relational/NoSQL).
• Familiarity with containerization tools (Docker, Kubernetes, Helm).
• Experience with performance testing tools (JMeter, Blazemeter) and Chaos Monkey Testing.
• Skilled in development and testing tools and frameworks (JUnit, UDF, Tophat, Cucumber, Groovy, Postman, REST Assured, Eclipse, Maven, Jenkins, IntelliJ).

• Cloud certification (AWS, GCP, Azure).
• Practical cloud-native development experience.
• In-depth knowledge of the financial services industry and their IT systems.
• Experience in creating and executing performance and chaos test scripts.
• Experience in or understanding of A/B Testing, Chaos Monkey Testing, Engineering principles.
• Effective communication across teams and management, with a proactive approach to process improvement.
• Strong system design, application development, and operational stability skills.