Lead Software Engineer: AI-Powered Cloud & Security

JPMorgan Chase & Co.

Jersey City (NJ)

On-site

USD 180,000 - 240,000

Full time

14 days+

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Job summary

JPMorgan Chase & Co. in Jersey City seeks a Lead Software Engineer within the Global Technology Infrastructure Platform. You will be a core technical contributor responsible for delivering trusted, scalable technology solutions across multiple business functions.

You will guide design reviews, drive automation and secure coding practices, mentor teams, and promote AI-assisted development to improve code quality and delivery speed while maintaining resiliency and security.

Qualifications

Demonstrated hands-on expertise in Hyper-V and OpenShift infrastructure with 4+ years of experience.
Hands-on experience in system design, application development, testing, and operational stability.
Advanced in one or more programming languages.
Proficiency in automation and continuous delivery methods.
Full SDLC expertise and understanding of agile practices (CI/CD, resiliency, security).

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
Develops secure 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
Adds to team culture of diversity, opportunity, inclusion, and respect
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.