Senior Java & Cloud Lead Engineer — AI-Driven & Secure

JPMorgan Chase; Columbus (OH); On-site; USD 157,000 - 215,000; Full time

Job summary

JPMorgan Chase is seeking a Lead Software Engineer - Java/Cloud Engineer in New York, NY, with a strong focus on secure, scalable software development. The role sits in Consumer & Community Banking's technology group, contributing as a core technical contributor to deliver trusted products.

You will lead development efforts, guide the team in AI-assisted engineering practices, and ensure adherence to secure coding, testing, and CI/CD standards while collaborating across vendor and internal

Qualifications

• 5+ years of hands-on software engineering.
• Experience delivering design, development, testing and operations.
• Java and cloud tech proficiency.
• Experience with AI-assisted development tools.

Responsibilities

• Executes creative software solutions and troubleshooting beyond routine approaches.
• Develops secure, high-quality production code and reviews teammates' code.
• Drives enterprise AI-assisted engineering practices to improve quality and speed.
• Applies SDLC tools and AI-assisted development to improve automation value.
• Identifies opportunities to automate recurring issues for stability.
• Leads evaluation sessions with vendors and internal teams on architecture and applicability.

Skills

Java

Cloud technologies

AI-assisted engineering

CI/CD

Agile methodologies

Code reviews

Tools

Splunk

Dynatrace

Postman

Spring Framework

SQL/NoSQL databases

Job description

JPMorgan Chase is seeking a Lead Software Engineer - Java/Cloud Engineer in New York, NY, with a strong focus on secure, scalable software development. The role sits in Consumer & Community Banking's technology group, contributing as a core technical contributor to deliver trusted products.

You will lead development efforts, guide the team in AI-assisted engineering practices, and ensure adherence to secure coding, testing, and CI/CD standards while collaborating across vendor and internal