RESPONSIBILITIES & TASKS:
AI Solution Development
- Design, develop, test, and deploy AI/ML models supporting business and operational outcomes.
- Build and maintain AI services, APIs, and microservices for enterprise consumption.
- Develop Generative AI and Agentic AI solutions using approved enterprise platforms and frameworks.
- Implement Retrieval Augmented Generation (RAG) architectures and knowledge retrieval solutions.
- Develop prompt engineering, evaluation, and optimization approaches for AI systems.
AI Platform Engineering and MLOps
- Develop and maintain AI model deployment pipelines and model lifecycle processes.
- Build automated testing, deployment, monitoring, model versioning, and release management capabilities.
- Support production deployment of models and AI services aligned to enterprise architecture standards.
Data Engineering and Integration
- Design and develop data pipelines required for AI model training and inference.
- Integrate AI solutions with enterprise applications, cloud platforms, APIs, databases, and data warehouses.
- Support data preparation, feature engineering, and operationalization of AI models.
AI Operations, Monitoring, and Continuous Improvement
- Monitor model performance, accuracy, reliability, cost, and operational stability.
- Implement observability and monitoring frameworks for AI workloads.
- Investigate production issues, perform root-cause analysis, and implement corrective actions.
- Tune and optimize models and AI services for performance, quality, and usability.
Security, Governance, and Responsible AI
- Ensure AI solutions align with enterprise AI governance, information security, privacy, and data protection requirements.
- Apply responsible AI principles including fairness, transparency, explain ability, reliability, and human oversight.
- Support AI risk assessments, security reviews, and compliance documentation.
Collaboration and Enablement
- Work closely with business stakeholders, Data Scientists, solution architects, application teams, and platform engineers.
- Participate in AI use case discovery, design workshops, technical reviews, and implementation planning.
- Support knowledge sharing and AI capability development across regional subsidaries.
SKILLS & QUALIFICATIONS:
- Minimum 8 years of experience in software engineering, AI engineering, machine learning engineering, or related disciplines.
- Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Information Technology, or a related discipline.
- Experience developing production-grade AI/ML solutions, working with cloud-native platforms, and implementing machine learning models in enterprise environments.
Technical Skills
- Python
- Machine learning frameworks such as PyTorch, TensorFlow, and Scikit-Learn
- LLM and agent frameworks such as LangGraph, LangChain, Semantic Kernel, or AutoGen
- API development and microservices
- Vector databases and RAG architectures
- MLOps platforms, CI/CD, and model lifecycle management
- SQL and data engineering
- Cloud services across AWS, Azure, or GCP
- Container technologies such as Docker and Kubernetes
- Git and DevOps practices
Pay: RM7,800.00 - RM10,000.00 per month
Benefits:
- Dental insurance
- Health insurance
Application Question(s):
- Please share your notice period. Eg: Immediate/1 month/2 months
Education:
Experience:
- machine learning/AI engineering: 8 years (Preferred)
Work Location: Hybrid remote in Petaling Jaya