Lead Software Engineer: AI-Driven, Cloud-Native Finance

JPMORGAN CHASE BANK, N.A.; Singapore; On-site; SGD 150,000 - 210,000; Full time

Job summary

JPMorgan Chase Bank, N.A. in Singapore seeks a Lead Software Engineer to drive secure, scalable technology solutions within an agile team. You will contribute as a core technical actor across multiple domains to support the firm's objectives.

Responsibilities include designing, building and debugging production code, and leading AI-assisted engineering practices to improve quality, speed, and reliability. Cloud-native experience and strong SDLC knowledge are essential.

Qualifications

• 5+ years of software engineering experience with system design, development, testing, and operations.
• Bachelor’s degree in Computer Science or equivalent.
• Hands-on programming experience, especially in Java and Spring/Spring Boot.
• Experience with AI-assisted development tools and secure coding practices.
• Strong understanding of SDLC and agile methodologies, plus cloud-native work experience.

Responsibilities

• Executes creative software solutions, design, development, and troubleshooting.
• Develops secure, high-quality production code and reviews others' code.
• Leads adoption of AI-assisted engineering practices to improve quality and speed.
• Utilizes SDLC tools and automation to enhance value and reliability.
• Identifies and automates recurring issues to improve stability.
• Leads evaluation sessions with vendors and internal teams on architecture.

Skills

Java

Spring/Spring Boot

AI-assisted tools

CI/CD

Agile methodologies

Cloud native

Security

Education

Bachelor's Degree in Computer Science or equivalent

Tools

AWS

Terraform

Job description

JPMorgan Chase Bank, N.A. in Singapore seeks a Lead Software Engineer to drive secure, scalable technology solutions within an agile team. You will contribute as a core technical actor across multiple domains to support the firm's objectives.

Responsibilities include designing, building and debugging production code, and leading AI-assisted engineering practices to improve quality, speed, and reliability. Cloud-native experience and strong SDLC knowledge are essential.