Hands-On AI Engineer Intern — Build Real-World AI Systems

Augmentus; Singapore; On-site; SGD 90,000 - 140,000; Full time

Job summary

Augmentus in Singapore seeks a hands-on software engineer to build production-grade Python services and interfaces that power AI agents. You will implement tool integrations, data pipelines, and multi-step workflows while contributing to testing, logging, and robust documentation.

You will iteratively improve evaluation metrics, guardrails, and integration robustness, collaborating across data sources, services, and APIs.

Qualifications

• Solid CS fundamentals — data structures, algorithms, systems thinking.
• Self-driven problem solver — you don't wait to be told the next step.
• Good engineering habits — version control, testing, code review, structured debugging.
• Familiarity with APIs, backend concepts, and working in a terminal/CLI environment.
• Curiosity about AI/ML — you don't need deep experience, but you should have intuition for how LLMs work.

Responsibilities

• Build and maintain Python services and APIs that support the agent system and its automation workflows.
• Assist in developing and testing agent capabilities — tool integrations, data pipelines, multi-step workflows.
• Develop and improve evaluation, metrics, and guardrails for autonomous agents.
• Write clean, well-tested code with proper error handling, logging, and documentation.
• Integrate various data sources, services, and APIs into the agent's execution environment.
• Contribute to CI/CD pipelines, testing infrastructure, and developer tooling.

Skills

CS fundamentals

Problem solving

API design

Backend concepts

CLI experience

Debugging

Documentation

Education

Bachelor's degree in Computer Science

Tools

Git

CI/CD

Testing

Job description

Augmentus in Singapore seeks a hands-on software engineer to build production-grade Python services and interfaces that power AI agents. You will implement tool integrations, data pipelines, and multi-step workflows while contributing to testing, logging, and robust documentation.

You will iteratively improve evaluation metrics, guardrails, and integration robustness, collaborating across data sources, services, and APIs.