AI Engineer

Technology Bucket; Kuala Lumpur; On-site; MYR 120,000 - 210,000; Full time

Job summary

Technology Bucket in Kuala Lumpur seeks an experienced ML Engineer to design and deploy RAG pipelines and AI agents for advanced conversational AI products. You will work on model context protocols, vector databases, and prompt engineering to optimize tool use and data retrieval.

The role emphasizes hands-on development with Python, PyTorch/TensorFlow/JAX, and modern NLP/NLU/NLG techniques to deliver scalable AI capabilities across products.

Qualifications

• Degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.

Responsibilities

• Design, develop, and optimize robust RAG pipelines to facilitate effective information retrieval in conversational AI systems.
• Build and deploy intelligent AI agents capable of handling multi-turn conversations, executing autonomous tasks, and managing tool invocation based on user intent.
• Implement and maintain a Model Context Protocol to ensure seamless, standardized connectivity and data sharing between AI systems, external APIs, and databases.
• Manage and optimize vector databases and advanced indexing techniques to efficiently store and retrieve contextual data.
• Fine-tune large language models (LLMs) and apply advanced prompt engineering techniques to optimize for specific product use cases.
• Implement powerful NLP, NLU, and NLG techniques (sentiment analysis, entity recognition, text generation) to enhance product capabilities.
• Stay abreast of the latest ML and AI advancements, proactively suggesting new tools or frameworks to improve the tech stack.
• Partner with product and engineering teams to translate AI capabilities into practical, scalable applications.

Skills

RAG models development

Prompt engineering

Python programming

Production-ready ML deployment

Conversational AI

Education

Bachelor's degree in Computer Science/AI/ML or related field

Tools

Vector databases (Pinecone, Milvus, Weaviate)

PyTorch

TensorFlow

JAX

Job description

Jora Malaysia will close on 9th September 2026. Thank you for being with us, we are cheering you on as you continue your career journey.

Key responsibilities

• Model Development & Ownership: Design, develop, and optimize robust RAG (Retrieval-Augmented Generation) pipelines to facilitate effective information retrieval in conversational AI systems.
• AI Agent Deployment: Build and deploy intelligent AI agents capable of handling multi-turn conversations, executing autonomous tasks, and managing tool invocation based on user intent.
• System Integration: Implement and maintain a Model Context Protocol to ensure seamless, standardized connectivity and data sharing between AI systems, external APIs, and databases.
• Data Architecture: Manage and optimize vector databases and advanced indexing techniques to efficiently store and retrieve contextual data.
• LLM Optimization: Fine-tune large language models (LLMs) and apply advanced prompt engineering techniques to optimize for specific product use cases.
• NLP/NLU Implementation: Implement powerful NLP, NLU, and NLG techniques (sentiment analysis, entity recognition, text generation) to enhance product capabilities.
• Continuous Improvement: Stay abreast of the latest ML and AI advancements, proactively suggesting new tools or frameworks to improve the tech stack.
• Cross-Functional Collaboration: Partner with product and engineering teams to translate AI capabilities into practical, scalable applications.

Requirement

• Degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• 3+ years of industry experience in machine learning engineering, with a strong focus on building and deploying conversational AI or NLP solutions.
• Proven, hands-on experience developing RAG models, working with vector databases (e.g., Pinecone, Milvus, Weaviate), prompt engineering, and utilizing LLMs.
• Strong, production-level programming skills in Python and proficiency with ML frameworks such as PyTorch, TensorFlow, or JAX.