Lead Software Engineer - Java 17+, Spring Boot, AWS

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 Commercial & Investment Bank's Markets Technology -  Broker-Dealer group, you will be 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 break down technical problems
• Writes secure, high-quality production code and performs code reviews and debugging for peers.
• 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 outcome-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.
• 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.
• Serves as a function-wide subject matter expert in one or more areas of focus.
• Contributes to a team environment that values diversity, opportunity, inclusion, and mutual respect.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience in Java software development and architecture.
• Hands-on practical experience delivering system design, application development, testing, and operational stability.
• Strong written and oral communication and excellent presentation and influencing skills. Proven ability to collaborate with global agile teams.
• Strong knowledge in Core Java (Java 17+), Spring Boot, REST, Kafka, Microservices, Agile, DevOps. Good SQL/PL-SQL Skills and Hibernate/JPA. Deep experience in object oriented analysis and design (OOAD).
• 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.
• Proficient in all aspects of the Software Development Life Cycle.
• Exhibits strong analytical and problem-solving abilities, offering technical thought leadership in evaluating emerging technologies and influencing stakeholders, user groups, and global technology teams to solve complex problems at scale.
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.
• Experience working with cloud platforms such as AWS, Azure, or Google Cloud for deploying and managing AI solutions.

Preferred qualifications, capabilities, and skills

• Demonstrates a passion for architectural design that drives innovation across applications and teams, with extensive experience delivering large-scale enterprise software systems in regulated, real-world environments.
• Demonstrated experience in greenfield development and the ability to work autonomously in fast-paced, deadline-driven environments.
• Requires innovative, out-of-the-box thinking to design applications that transform existing mainframe functionalities and develop new features using distributed or modern technologies.
• Holds AWS certification(s) and has practical experience with AWS services, Spark, AWS Glue ETL, and Python. Practical experience with machine learning and AI technologies (such as Python, TensorFlow, and Scikit-learn) is a plus.
• Understanding of equities or fixed income products and familiarity with the trade lifecycle.
• Experience working with enterprise-scale data assets such as MDM, EDW, and data lakes, and navigating diverse technology landscapes and process/technology integration challenges. 
• Experience in leading or contributing to modernization projects involving migration of mainframe applications to distributed technologies.