- Kuala Lumpur Federal Territory Malaysia
R Systems Hiring! Full Time Data Engineer in Federal Territory - Ricebowl
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Job Description
Responsibilities
Hiring: Data Engineer / AI Engineer
We are looking for an experienced Data Engineer with 5+ years of overall experience, including at least 1–2 years of hands-on experience as an AI Engineer.
Role: Data Engineer / AI Engineer
Experience: 5+ years overall, with 1–2+ years in AI Engineering
Location: Malaysia
Employment Type: Full-time / Contract
Key Responsibilities
- Design, build and maintain scalable data pipelines and data platforms.
- Develop and optimize ETL/ELT pipelines for structured and unstructured data.
- Work with cloud data platforms, data lakes and data warehouses.
- Develop and integrate AI/ML solutions into data and business applications.
- Work with Generative AI, LLMs, RAG or AI-powered applications where applicable.
- Prepare, transform and manage datasets for AI/ML model development and deployment.
- Develop APIs and data services to support AI and analytics applications.
- Implement data quality, monitoring, governance and performance optimization.
- Collaborate with Data Scientists, AI Engineers, Software Engineers and Business teams.
- Troubleshoot data and AI pipeline issues and support production deployments.
Required Skills
- 5+ years of experience in Data Engineering
- 1–2+ years of hands-on AI Engineering experience
- Strong experience in Python and SQL
- Strong understanding of ETL/ELT and data pipeline development
- Experience with data lakes, data warehouses and cloud platforms
- Experience with Apache Spark / PySpark
- Experience with technologies such as Databricks, Azure, AWS or GCP
- Understanding of Machine Learning and AI concepts
- Hands-on exposure to Generative AI / LLM / RAG solutions
- Experience with APIs, microservices and cloud-based applications
- Strong problem-solving and analytical skills
Nice to Have
- Experience with Azure OpenAI, AWS Bedrock, Google Vertex AI or similar AI platforms
- Experience building RAG pipelines and vector databases
- Knowledge of ML/AI deployment and MLOps
- Experience with Docker, Kubernetes and CI/CD
- Knowledge of Kafka or other streaming technologies
- Experience working with production-grade AI applications
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