AI-Driven Mainframe Systems Engineer I

MetLife

Kuala Lumpur

On-site

MYR 120,000 - 180,000

Full time

7 days ago
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Job summary

MetLife is seeking a Core Systems Software Engineer to develop and maintain mainframe-based insurance systems. You will help modernize development environments, implement AI-assisted tooling, and work with teams across Japan, Malaysia, and India.

The candidate should have strong COBOL/JCL/DB2 experience, a Bachelor’s degree, and a track record of solving complex problems with cross-functional collaboration in a regulated financial context.

Qualifications

  • Bachelor’s degree or equivalent.
  • 3+ years of software development experience with mainframe environments (COBOL, JCL, DB2).
  • Experience integrating mainframe solutions with modern platforms.
  • Experience in regulated financial industry space desirable.
  • Strong problem-solving, analytical, and collaboration skills.
  • Experience with Agile development preferred.
  • Practical experience using AI-assisted development tools to improve coding, testing, and troubleshooting.

Responsibilities

  • Develop and maintain mainframe applications.
  • Leverage AI-assisted tools to improve code quality and automate testing.
  • Translate business requirements into system specifications.
  • Improve batch and online processing performance; handle incidents.
  • Prepare release plans and operational manuals.
  • Ensure security and regulatory compliance in design and operations.
  • Collaborate with delivery teams across Japan, Malaysia and India.

Skills

COBOL
JCL
DB2
AI tooling
CI/CD
Agile
Problem solving
Collaboration

Education

Bachelor’s degree or equivalent

Job description

MetLife is seeking a Core Systems Software Engineer to develop and maintain mainframe-based insurance systems. You will help modernize development environments, implement AI-assisted tooling, and work with teams across Japan, Malaysia, and India.

The candidate should have strong COBOL/JCL/DB2 experience, a Bachelor’s degree, and a track record of solving complex problems with cross-functional collaboration in a regulated financial context.

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