AI Engineer
23 hours ago
Location:
Bukit Bintang
Industry:
Insurance
Employment Type:
Contract (12months)
About the Role
We are seeking a highly skilled
AI Engineer
to join our team and support the development, enhancement, and integration of AI solutions across the organization. This role will play a key part in advancing our AI and analytics capabilities, implementing automation, and ensuring governance and compliance within the insurance domain.
Key Responsibilities
- Enhance and support the AI & analytics platform using Infrastructure-as-Code tools such as
Terraform
and
AWS CDK
, ensuring alignment with existing cloud architecture. - Manage the
end-to-end AI/ML model lifecycle
, including training, evaluation, deployment, monitoring, inference, and integration into downstream applications. - Participate in
RFI/RFP processes
, vendor evaluation, and integration of third-party AI solutions in accordance with technology and governance standards. - Develop and implement
generative AI and LLM-based solutions
, including chatbots, AI agents, and automation tools. - Automate core insurance processes, including OCR document extraction, automated adjudication, fraud detection, eligibility checks, and workflow automation for claims and underwriting.
- Collaborate with data engineers, business analysts, and stakeholders to integrate AI outputs into business operations and reporting workflows.
- Ensure adherence to
AI governance
, responsible AI practices, data privacy regulations, and model explainability requirements. - Lead the development of ground-truth datasets, labeling processes, performance metrics, and analytics for model improvement.
Requirements
- Bachelor's Degree or above in
Data Science, Computer Science, Statistics, Mathematics
, or a related discipline. - Minimum
4 years of experience
in AI/ML engineering, data science, or related fields. - Proficiency in
Python
and machine learning frameworks such as scikit-learn, XGBoost, PyTorch, TensorFlow, and LangChain. - Hands-on experience with
Generative AI and LLM technologies
(e.g., LangChain, LlamaIndex, NLP, fine-tuning). - Strong experience in
AWS cloud deployments
, MLOps practices (CI/CD, monitoring), and lifecycle automation. - Familiarity with
event-driven and serverless architectures
, including AWS Lambda and Fargate.
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