Artificial Intelligence Engineer

UST Malaysia; George Town; Híbrido; MYR 90.000 - 150.000; Jornada completa

Descripción de la vacante

UST Malaysia is seeking a qualified AI/ML software engineer to develop and refine AI-powered applications using LLMs and Generative AI. You will design and optimize RAG pipelines for knowledge retrieval and answer generation, and build AI agents capable of autonomous reasoning and task execution.

You will also integrate MCP tools to connect AI agents with enterprise systems, evaluate and benchmark models, and maintain robust prompt strategies to ensure high-quality responses across cloud

Formación

• Bachelor's degree in CS/Software Engineering/AI/Data Science or related field.
• Fundamental understanding of LLMs and Generative AI concepts.
• Basic programming in Python and REST API know-how.
• Familiarity with GitHub and software development lifecycle basics.
• Understanding of REST APIs and system integration concepts.
• Interest in prompt engineering and AI application development.

Responsabilidades

• Develop and enhance AI-powered applications using LLMs and Generative AI.
• Design and optimize RAG pipelines for knowledge retrieval and Q&A.
• Build AI agents with autonomous reasoning, planning, and execution.
• Integrate MCP tools to connect AI agents with enterprise systems.
• Evaluate, fine-tune, and benchmark LLMs for business use cases.
• Maintain prompt engineering strategies to improve AI quality.
• Work with vector databases, embeddings, and semantic search.
• Conduct testing, debugging, and performance analysis.
• Document designs, implementation guides, and architectures.
• Support deployment and maintenance of AI services in cloud environments.
• Involve in all development stages from architecture to implementation.

Conocimientos

Python programming

REST APIs

Problem solving

Analytical skills

Prompt engineering

Learning agility

LLMs/Gene AI concepts

Educación

Bachelor's degree in Computer Science/Software Engineering/AI/Data Science

Herramientas

OpenAI

Azure OpenAI

Claude

Gemini

LangGraph

LangChain

AutoGen

MCP (Model Context Protocol)

FastAPI

Python backend development

Vector databases / Embeddings / Semantic search

Descripción del empleo

• Develop and enhance AI-powered applications using LLMs and Generative AI technologies.
• Design, implement, and optimize RAG pipelines for intelligent knowledge retrieval and question-answering systems.
• Build and integrate AI agents capable of autonomous reasoning, planning, and task execution.
• Develop and integrate MCP tools to connect AI agents with enterprise systems, databases, and engineering services.
• Assist in evaluating, fine-tuning, and benchmarking LLMs for specific business use cases.
• maintain prompt engineering strategies to improve AI response quality and reliability.
• Work with vector databases, embeddings, and semantic search technologies.
• Conduct testing, debugging, and model performance analysis to ensure AI solution quality.
• Document technical designs, implementation guides, and AI solution architectures.
• Support deployment and maintenance of AI services in cloud and enterprise environments.
• Involve in all the stages of development from architecting to implementing
• Skillset -Bachelor's degree (or pursuing final year) in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or related fields.
• Basic understanding of LLMs and Generative AI concepts.
• Familiarity with programming languages such as Python.
• Knowledge of GitHub and software development lifecycle practices.
• Understanding of REST APIs and system integration concepts.
• Familiarity with prompt engineering and AI application development.
• Strong problem-solving and analytical skills.
• Eagerness to learn emerging AI technologies and frameworks.

Preferred Skills

• Experience with OpenAI, Azure OpenAI, Claude, Gemini, or open-source LLMs.
• Knowledge of Agentic AI frameworks (LangGraph, LangChain, CrewAI, AutoGen, etc.).
• Familiarity with RAG, vector databases, embeddings, and semantic search.
• Understanding of MCP (Model Context Protocol) concepts and tool integrations.
• Experience with FastAPI, Python backend development, or cloud services.
• Exposure to AI evaluation, model benchmarking, or LLMOps practices