Associate Software Engineer, AI-Driven Metrics Platform

Candidate Experience Site - Lateral; Singapore; On-site; SGD 110,000 - 150,000; Full time

Job summary

Goldman Sachs in Singapore is seeking an Associate Software Engineer to join the Metrics & Analytics Platform Engineering team. You will contribute to building scalable risk metrics engines and complex workflows, with hands-on coding and collaboration with cross-functional partners.

The role emphasizes high-performance systems, cloud-first architecture, modern SDLC practices, and close interaction with quantitative engineers and product managers.

Qualifications

• Min 4 years of hands-on software development experience.
• Backend: Java, Spring Boot, Python.
• Experience with CI/CD, automated testing and code reviews.
• Cloud experience, preferably AWS, with high-availability patterns.
• Experience implementing or integrating AI-enabled tools or platforms.
• Bachelor’s degree in CS, Engineering, or equivalent.
• Strong analytical and problem-solving skills.
• Excellent communication with technical and non-technical stakeholders.

Responsibilities

• Build scalable metrics engines delivering high-throughput data and calculations.
• Engineer robust risk workflows for evaluating scenarios and credit risk.
• Contribute to AI-enabled, cloud-first architecture initiatives.
• Write production-quality code and perform unit tests.
• Follow modern SDLC practices and participate in code reviews.
• Collaborate with quantitative engineers, tech leads, and product managers.

Skills

Java

Spring Boot

Python

CI/CD

Unit testing

Git

Debugging

Education

Bachelor's degree in Computer Science or related field

Tools

AWS

Git

JUnit

Job description

Goldman Sachs in Singapore is seeking an Associate Software Engineer to join the Metrics & Analytics Platform Engineering team. You will contribute to building scalable risk metrics engines and complex workflows, with hands-on coding and collaboration with cross-functional partners.

The role emphasizes high-performance systems, cloud-first architecture, modern SDLC practices, and close interaction with quantitative engineers and product managers.