AI Engineer - Insurance Decision Intelligence
- Compensation
- Not disclosed
- Location
- Kuala Lumpur
- Work setup
- Onsite
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Ai engineering
- Posted
Skills
Must have
- • 3-5 years of experience in machine learning, AI engineering, or predictive analytics (juniors may be considered)
- • Strong proficiency in Python, including Pandas and NumPy, plus experience with PyTorch, TensorFlow, or scikit-learn
- • Experience building predictive models using gradient boosting (XGBoost, LightGBM), random forest, ensemble models, or anomaly detection
- • Solid grasp of feature engineering, model evaluation, and optimisation, with experience deploying models into production and exposing them via APIs
- • Familiarity with model lifecycle management, including monitoring, retraining, and version control
- • Knowledge of RAG approaches, document intelligence, and PII protection safeguards
- • Advantageous: insurance, banking, or fintech experience, risk analytics, and explainability tools such as SHAP or LIME
Full description
About Us
Tentacle Tech is an IT and software development consulting company serving some of Malaysia's largest enterprises. We deliver technology solutions, software development services, and IT consulting across multiple industries. We are looking for a talented professional to join our growing team.
The Role
As an AI Engineer focused on Insurance Decision Intelligence, you will build production-grade predictive models and AI services that support high-volume operational decisions in the finance sector. Working closely with business stakeholders and data platform teams, you will turn real-world insurance challenges into scalable AI solutions that improve risk assessment, operational efficiency, and customer outcomes. This is a hybrid position where your work will have a visible, measurable impact.
What You'll Do
- Develop and deploy machine learning models supporting underwriting, claims, fraud detection, and customer analytics
- Perform feature engineering and model experimentation using policy, claims, and customer datasets
- Own the lifecycle of AI models from experimentation through production deployment and monitoring
- Work with business teams to identify opportunities where AI can improve decision quality and operational efficiency
- Contribute to internal standards for AI model development, governance, and monitoring
- Support the development of the Business AI roadmap
What We're Looking For
- 3-5 years of experience in machine learning, AI engineering, or predictive analytics (juniors may be considered)
- Strong proficiency in Python, including Pandas and NumPy, plus experience with PyTorch, TensorFlow, or scikit-learn
- Experience building predictive models using gradient boosting (XGBoost, LightGBM), random forest, ensemble models, or anomaly detection
- Solid grasp of feature engineering, model evaluation, and optimisation, with experience deploying models into production and exposing them via APIs
- Familiarity with model lifecycle management, including monitoring, retraining, and version control
- Knowledge of RAG approaches, document intelligence, and PII protection safeguards
- Advantageous: insurance, banking, or fintech experience, risk analytics, and explainability tools such as SHAP or LIME
What We Offer
- Competitive salary
- Hybrid work arrangement for better work-life balance
- Hands-on exposure to large-scale enterprise AI projects