About this role
J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. As a Lead Software Engineer at JPMorganChase within IP Product Management, 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.
Job Responsibilities
• 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.
• Partner with product managers, security, data, and platform teams to align on priorities and deliver secure, compliant solutions.
• Owns remediation of engineering hygiene issues (e.g. vulnerability findings, dependency upgrades, test coverage gaps) and drives sustainable remediation through automation, standards and measurable quality targets.
Required qualifications, capabilities, and skills
• Formal training or certification on software engineering concepts and applied experience.
• Solid troubleshooting skills with attention to detail; ability to balance delivery speed with quality and reliability.
• Strong hands-on experience in Java software engineering.
• Front-end visualization experience using React (or similar).
• Practical experience with AWS and cloud-native infrastructure: AWS ECS/EKS/S3, Kubernetes, containers, and terraform for infrastructure as code.
• 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.
• Proven experience across the SDLC: design, development, testing, deployment, and operations in a large corporate environment.
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.
• Effective communicator and team player; comfortable collaborating across engineering, product, and operations teams.
Preferred qualifications, capabilities, and skills
• Proficiency in Python for data processing, automation, and service integration (e.g., ETL/ELT jobs, orchestration, or platform tooling).
• Demonstrated expertise in Agile/Scrum practices, including facilitating ceremonies (standups, planning, refinement, reviews, retrospectives), backlog hygiene, and flow-based execution (Scrum).
• Working knowledge of Snowflake data warehousing.