AI Engineer

Kenanga Group; Kuala Lumpur; On-site; MYR 120,000 - 180,000; Full time

Job summary

Kenanga Group seeks an AI Engineer to embed Generative AI into its digital platforms. You will design, develop, deploy, and continuously improve AI/GenAI solutions to drive business value, efficiency, and innovation while aligning with enterprise architecture and data governance.

Key responsibilities include AI solution engineering, MLOps & platform integration, data governance & risk management, and ongoing self-development through trainings and knowledge sharing.

Qualifications

• Degree in Computer Science, AI, ML, Data Science or related field.
• 4-8 years on platform administration field.
• Hands-on experience delivering AI/ML solutions from ideation to production.

Responsibilities

• AI Solution Engineering: design and deliver AI/GenAI solutions including NLP, recommendation systems, and multi-modal models.
• MLOps & Platform Integration: implement CI/CD, containerization, Kubernetes, and model versioning; define GenAI strategy and roadmap.
• Data Governance & Risk Management: ensure AI lifecycle governance, privacy protection, and regulatory alignment.
• Self-Development: attend trainings; document solutions and share best practices; upskill on emerging AI technologies.

Skills

AI/GenAI

NLP

Recommendation systems

Multi-modal models

Education

Degree in Computer Science, AI, Machine Learning, Data Science or related field

Tools

CI/CD

Containerization

Kubernetes

Model versioning

Job description

The AI Engineer plays a key role in embedding Generative AI capabilities into the Bank’s digital and technology platforms. This role is responsible for the design, development, deployment, and continuous improvement of AI and GenAI solutions that drive business impact, operational efficiency, and innovation while ensuring alignment with enterprise architecture, data governance,

and regulatory requirements.

Key Responsibilities:

1.AI Solution Engineering

• Design and deliver AI/GenAI solutions including NLP, recommendation systems, and multi-modal models.

2.MLOps & Platform Integration

• Implement CI/CD, containerization, Kubernetes, and model versioning aligned to enterprise standards.
• Define and evolve GenAI strategy, roadmap, and ethical adoption. Engage senior stakeholders and secure sponsorship.
• Build, deploy and monitor generative models; integrate models into production platforms with feedback loops

5.Data Governance & Risk Management

• Ensure AI lifecycle governance, privacy protection, and regulatory alignment.

6.Self- Development

• Attend relevant trainings and compulsory courses.
• Document solutions, share best practices, and continuously upskill on emerging AI technologies

Qualifications, Experience and Knowledge/Skills/Attributes

• Degree in Computer Science, AI, Machine Learning, Data Science or related field
• 4-8 years on platform administration field
• Hands-on experience delivering AI / ML solutions from ideation to production