Lead Software Engineer - Java with Agentic AI

JPMorgan Chase & Co.; Chicago (IL); On-site; USD 140,000 - 190,000; Full time

Job summary

JPMorganChase in Chicago seeks a Lead Software Engineer to join the Consumer & Community Banking agile team, delivering trusted, scalable technology products in a secure environment.

You will drive AI-assisted engineering practices, mentor engineers, and develop production-grade code using Core Java, J2EE, and Spring Boot within a modern SDLC framework.

Qualifications

• Formal training or certification on software engineering concepts and 8+ years applied experience.

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.

Skills

AI-assisted development

Leadership

Secure coding

Core Java

J2EE

Spring Boot

Agile methodologies

CI/CD

Tools

AWS

EKS

Kafka

OpenAPI

Swagger

JSON Schema

AsyncAPI

Job description

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 JPMorganChase within the Consumer & Community Banking, 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
• 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.
• Lead the rollout of BDD and SDD practices across product and engineering teams
• Build SDD tooling that derives contract checks, mocks, and validation from machine-readable specs (OpenAPI/Swagger, JSON Schema, AsyncAPI for Kafka) as the source of truth.
• Develops secure and high-quality production code, and reviews and debugs code written by others
• 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 outcomes-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

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 8+ years applied experience
• 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
• Strong software engineer with hands-on experience using AI coding assistants/agents to design, implement, test, and debug production code
• Proficient in Core Java, J2EE, and Spring Boot with strong coding skills.
• Experienced in build and deployment processes
• Knowledgeable in EKS, Kafka, and message parsers
• Proficient in all aspects of the Software Development Life Cycle
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security

Preferred qualifications, capabilities, and skills

• Experience using AWS - EKS and Bedrock
• AI-Agentic approach in automation