Lead Software Engineer — AI-Driven Platform & Security

JPMorgan Chase & Co.

Chicago (IL)

On-site

USD 150,000 - 190,000

Full time

7 days ago

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Job summary

JPMorgan Chase & Co. within the Commercial & Investment Bank's Digital & Platform Services group is seeking a Senior Lead Software Engineer to contribute to agile teams delivering trusted technology products across secure, scalable platforms.

You will design, develop, and review production code, lead architectural evaluations, and advance AI-assisted engineering practices to improve code quality, speed, and reliability across critical business systems.

Qualifications

Formal training or certification on software engineering concepts and 5+ years applied experience.
Advanced in coding Java Spring Boot and Java Core Microservices Architecture.
Experienced in researching business requirements and developing a tool to solve the business' problems.
Advanced knowledge of SQL and noSQL Databases.
Advanced knowledge of Kafka or restAPI Messaging Services.
Hands-on practical experience delivering system design, application development, testing, and operational stability.
Proficient in all aspects of the Software Development Life Cycle.
Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.
In-depth knowledge of the financial services industry and their IT systems.
Demonstrated experience leading effective use of approved AI-assisted software development tools with validation standards.

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.
Research business requirements and develop tools to solve the business' problems.
Develops secure high-quality production code, and reviews and debugs code written by others.
Identifies opportunities to automate remediation of recurring issues to improve stability.
Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of designs.
Leads communities of practice across Software Engineering to drive awareness of new technologies.
Adds to team culture of diversity, opportunity, inclusion, and respect.
Drives team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and outcomes, with validation standards.
Applies knowledge of SDLC tools, including AI-assisted development and automation capabilities, to improve value.