Job Description

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As a Senior Lead Software Engineer at JPMorganChase within the Commercial & Investment Bank Payments Team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities

• Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
• Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
• Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
• Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
• Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
• Contributes to software engineering communities of practice and events that explore new and emerging technologies

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Hands-on practical experience in system design, application development, testing, and operational stability
• Proficient in coding Java (Spring boot), Postgress, Kubernetes with well-versed with various design principles such as SOLID, microservices
• Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
• Hands-on practical experience on developing high performance, scalable and resilient application using Java full stack
• Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
• Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (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 senior engineers/leads on compliant usage patterns and controls.
• Ability to tackle design and functionality problems independently with little to no oversight

Preferred qualifications, capabilities, and skills

• Familiarity with modern front-end technologies and their impact on end-to-end system performance
• Exposure to CI/CD pipelines and integrating performance testing into automated workflows
• Experience with containerization and microservices architectures
• Strong interest in AI/ML-driven performance analytics
• Knowledge of caching strategies and distributed systems