AI Transformation Engineer — Data Pipelines & Automation

Starhub Ltd; Singapore; On-site; SGD 52,000 - 90,000; Full time

Job summary

StarHub Ltd. invites an AI Transformation Engineer to translate AI ideas into practical solutions for network and operations teams. You will work hands-on with senior engineers to build, test, and deploy use cases that automate workflows and surface insights from data.

This early-career role offers broad exposure to data pipelines, machine learning, LLM-based tooling, and process automation, while ensuring solutions are reliable, compliant, and auditable as per PDPA guidelines.

Qualifications

• Degree in CS/DS/Engineering or related field.
• 0–2 years; internships welcome in AI, data, or automation.
• Working knowledge of Python and ML; basic LLM concepts.
• Exposure to telecom or network data, cloud or LLM tooling.
• Foundational familiarity across Python, Git, APIs, Pandas/NumPy

Responsibilities

• Build and deliver AI solutions; support design, development and testing.
• Build and maintain data pipelines for AI models.
• Develop prompts and lightweight LLM integrations.
• Identify repetitive tasks and automate workflows.
• Implement production automations and monitor performance.
• Run experiments and measure model accuracy, latency, and reliability.
• Document data sources and design decisions; ensure reproducibility.
• Collaborate with data, network, and platform engineers; participate in reviews.
• Follow PDPA and internal data-governance practices.

Skills

Python

ML Fundamentals

LLMs/SLMs

RAG/Prompting

Data Pipelines

REST APIs

Cloud Basics

Git/Version Control

Pandas/NumPy

Education

Bachelor's degree in CS/DS/Engineering

Tools

LLM Tooling

Cloud Platforms

Data Visualization

Job description

StarHub Ltd. invites an AI Transformation Engineer to translate AI ideas into practical solutions for network and operations teams. You will work hands-on with senior engineers to build, test, and deploy use cases that automate workflows and surface insights from data.

This early-career role offers broad exposure to data pipelines, machine learning, LLM-based tooling, and process automation, while ensuring solutions are reliable, compliant, and auditable as per PDPA guidelines.