AI Engineer- (GenAI, LLM) | 1 Year Contract

TG Malaysia; Kuala Lumpur; On-site; MYR 120,000 - 180,000; Full time

Job summary

TG Malaysia, a leading regional insurer, seeks an AI Engineer to develop and deploy ML solutions across underwriting, claims analytics and fraud detection. You will analyze data, engineer features, and optimize models on large datasets while building AI tools to extract information from insurance documents.

You will collaborate with business stakeholders to drive AI governance and best practices, with production deployment and monitoring as part of the lifecycle.

Qualifications

• 3 to 5 years of experience in AI, ML, Data Science or Predictive Analytics.
• Strong Python programming with Pandas and NumPy.
• Experience with ML frameworks such as Scikit-learn, PyTorch, or TensorFlow.
• Knowledge of predictive modeling techniques and anomaly detection.
• Experience deploying ML models into production and monitoring.
• Familiarity with SHAP or LIME is advantageous.

Responsibilities

• Develop and deploy ML models for underwriting, claims analytics and fraud detection.
• Perform data analysis, feature engineering and model optimization on large data sets.
• Build AI solutions for extracting information from insurance documents.
• Support full ML lifecycle from development to production monitoring.
• Collaborate with stakeholders to identify AI-driven improvement opportunities.
• Contribute to AI governance, standards and best practices.

Skills

Python

Pandas

NumPy

Scikit-learn

PyTorch

TensorFlow

XGBoost

LightGBM

Random Forest

Ensemble Models

Anomaly Detection

Model deployment

Model monitoring

Retraining

Explainable AI

Job description

Our client is a leading regional insurance and takaful provider with a strong presence across ASEAN markets. Backed by an established financial services group and a global insurance partner, the organization offers a wide range of life insurance, general insurance, family takaful, and general takaful solutions to individuals, businesses, and corporate clients.

About the Role

We are looking for an AI Engineer to develop and deploy machine learning and AI solutions that support data-driven decision making across the insurance business. You will work on projects involving underwriting, fraud detection, claims processing, customer analytics, and document intelligence. This is a great opportunity for candidates with experience in machine learning, predictive analytics, or AI engineering who are interested in solving real-world business challenges at scale.

Key Responsibilities

• Develop and deploy machine learning models for underwriting, claims analytics, and fraud detection.
• Perform data analysis, feature engineering, and model optimization using large datasets.
• Build AI solutions for extracting information from insurance-related documents.
• Support the full AI model lifecycle, from development and testing to production deployment and monitoring.
• Collaborate with business stakeholders to identify opportunities for AI-driven improvements.
• Contribute to AI governance, standards, and best practices.

Requirements

• 3 to 5 years of experience in AI, Machine Learning, Data Science, or Predictive Analytics.
• Junior candidates with relevant project experience are encouraged to apply.
• Strong Python programming skills, including Pandas and NumPy.
• Experience with machine learning frameworks such as Scikit-learn, PyTorch, or TensorFlow.
• Knowledge of predictive modeling techniques such as XGBoost, LightGBM, Random Forest, Ensemble Models, or Anomaly Detection.
• Experience deploying machine learning models into production environments.
• Understanding of model monitoring, version control, and retraining processes.
• Experience with explainable AI techniques such as SHAP or LIME is an advantage.

Preferred Experience

• Exposure to insurance, banking, fintech, or risk analytics domains.
• Experience with fraud detection, risk scoring, customer analytics, or decision support systems.
• Familiarity with document intelligence solutions, OCR, computer vision, or LLM based document processing.
• Knowledge of RAG (Retrieval-Augmented Generation) and enterprise knowledge retrieval solutions.

Example Projects

• Insurance fraud detection and risk prediction.
• Underwriting risk scoring models.
• Claims and policy document automation.
• Customer segmentation and retention analytics.
• Detection of fraud networks and abnormal claim patterns.