About this role
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.