Lead Software Engineer-Java with Agentic AI

JPMorganChase•Chicago, IL

About The Position

As a Lead Software Engineer at JPMorganChase within Consumer & Community Banking, you will contribute to an agile team building and delivering secure, stable, scalable technology products. You will develop critical technology solutions across multiple technical areas in support of business objectives, using creative problem-solving and technical expertise. The role includes promoting enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes. You will establish standards for validating AI-generated work, including secure coding, peer review, and automated testing, and encourage reuse of effective approaches. You will also lead the rollout of BDD and SDD practices across product and engineering teams and build tooling that derives contract checks, mocks, and validation from machine-readable specifications such as OpenAPI/Swagger, JSON Schema, and AsyncAPI for Kafka. You will develop secure, high-quality production code; review and debug others’ code; improve operational stability by eliminating or automating recurring issues; lead technical evaluations with vendors, startups, and internal teams; and foster communities of practice that increase awareness and adoption of leading-edge technologies.

Requirements

Formal training or certification in software engineering concepts and at least 8 years of applied experience.
Demonstrated experience leading effective use of approved AI-assisted software development tools for coding, code review, test acceleration, or troubleshooting, including setting expectations for validating outputs for correctness, performance, and security.
Strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and resiliency and security expectations.
Experience coaching engineers on safe, compliant adoption of AI-assisted tools in delivery practices.
Hands-on experience using AI coding assistants or agents to design, implement, test, and debug production code.
Proficiency in Core Java, J2EE, and Spring Boot, with strong coding skills.
Experience with build and deployment processes.
Knowledge of EKS, Kafka, and message parsers.
Proficiency in all aspects of the Software Development Life Cycle.
Advanced understanding of agile methodologies, including CI/CD, application resiliency, and security.

Nice To Haves

Experience using AWS EKS and Bedrock with an AI-agentic approach to automation.
Experience in performance engineering.

Responsibilities

Execute creative software solutions, including design, development, and technical troubleshooting, using approaches beyond routine methods to solve technical problems.
Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes.
Establish consistent validation standards for AI-assisted work, including secure coding, peer review, and automated testing, and promote reuse of effective patterns.
Use Software Development Life Cycle tools, including authorized AI-assisted development and automation capabilities, to improve the value of automation.
Lead rollout of BDD and SDD practices across product and engineering teams.
Build SDD tooling that derives contract checks, mocks, and validation from machine-readable specifications, including OpenAPI/Swagger, JSON Schema, and AsyncAPI for Kafka.
Develop secure, high-quality production code and review and debug code written by others.
Identify opportunities to eliminate or automate remediation of recurring issues to improve software and systems operational stability.
Lead evaluation sessions with external vendors, startups, and internal teams to assess architectural designs, technical credentials, and applicability to existing systems and information architecture.
Lead Software Engineering communities of practice to promote awareness and use of new and leading-edge technologies.