Lead Full-Stack Engineer (React) - AI-Driven, Scalable Infra

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

Job summary

JPMorgan Chase & Co. in Plano, TX is seeking a Lead Software Engineer to own the design, delivery, and operation of enterprise-scale infrastructure services.

You will be a core technical contributor shaping AI-native practices across the SDLC while maintaining secure, reliable, and scalable systems. The role requires hands-on coding in multiple languages, producing high-quality production code, and mentoring engineers.

Qualifications

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Hands-on experience delivering design, development, testing, and operational stability.
• Experience leading AI-assisted software development tools and validating outputs.
• Strong understanding of responsible AI use in engineering workflows and security.

Responsibilities

• Executes creative software solutions and troubleshooting across complex problems.
• Establish AI-native engineering practices with robust validation standards.
• Work across the SDLC using AI-assisted development and incident analysis.
• Drive adoption of AI-assisted practices to improve code quality and speed.
• Apply SDLC tools to improve automation and value realization.
• Own design, delivery, and operation of enterprise-scale infrastructure services.
• Write and review production code with a hands-on approach.
• Identify and automate remediation of recurring issues for stability.
• Lead evaluation sessions with vendors and internal teams on architecture.
• Lead communities of practice to promote new technologies.
• Contribute to an inclusive team culture and respect.

Skills

Python

Go

Java

C++

Rust

React

CI/CD

Security

Tools

Linux

Kubernetes

AWS

Job description

JPMorgan Chase & Co. in Plano, TX is seeking a Lead Software Engineer to own the design, delivery, and operation of enterprise-scale infrastructure services.

You will be a core technical contributor shaping AI-native practices across the SDLC while maintaining secure, reliable, and scalable systems. The role requires hands-on coding in multiple languages, producing high-quality production code, and mentoring engineers.