AI Engineer (ML, LLM, RAG & Agentic AI) | | UAE

Job Title:

AI Engineer (ML, LLM, RAG & Agentic AI) | Sundus Global | Abu Dhabi, UAE

Recruiting Company:
Sundus Global

Job Location:

Abu Dhabi, United Arab Emirates

Job Type: Full-Time

Experience

Required:

2+ Years

Education:

Bachelor’s Degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field

Language Requirement:
English

Sundus Global is seeking an AI Engineer to develop and deploy next-generation Artificial Intelligence solutions, including Machine Learning, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI systems. This role offers an exciting opportunity to work on cutting-edge AI initiatives within a rapidly evolving technology environment in Abu Dhabi.

As an AI Engineer, you will be responsible for designing, developing, deploying, and optimizing AI-driven applications and intelligent automation solutions. You will work on advanced machine learning models, natural language processing systems, generative AI applications, and agent-based workflows that enable business transformation and operational efficiency.

The ideal candidate will possess strong software engineering skills combined with practical experience in machine learning frameworks, modern AI architectures, and enterprise integration technologies. You will collaborate with data scientists, software engineers, cloud architects, and business stakeholders to deliver scalable and production-ready AI solutions.

• Design and develop Machine Learning and Artificial Intelligence solutions.
• Build, train, evaluate, and deploy machine learning models.
• Develop and optimize LLM-powered applications and workflows.
• Design and implement Retrieval-Augmented Generation (RAG) architectures.
• Build Agentic AI solutions using autonomous and multi-agent frameworks.
• Integrate AI services with enterprise platforms through REST APIs.
• Develop NLP-based applications including conversational AI and intelligent assistants.
• Deploy and manage AI workloads on cloud or on-premises infrastructure.
• Optimize AI model performance, scalability, and reliability.
• Support model monitoring, maintenance, and lifecycle management.
• Collaborate with development teams to integrate AI capabilities into business applications.
• Ensure AI solutions adhere to security, governance, and operational standards.

• Bachelor’s Degree in Computer Science, AI, Data Science, Software Engineering, or a related field.
• Minimum 2 years of experience in AI and Machine Learning development.
• Strong proficiency in Python programming.
• Hands-on experience with:
  • Scikit-learn
  • Py Torch
  • Tensor Flow
• Strong understanding of Machine Learning concepts and workflows.
• Knowledge of Natural Language Processing (NLP).
• Experience across the complete AI lifecycle including:
  • Model Training
  • Model Evaluation
  • Model Deployment
• Experience with REST API integration and development.
• Familiarity with Git and version control systems.

• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• Agentic AI Workflows
• Generative AI Applications
• NLP Solutions
• Intelligent Automation
• Conversational AI
• AI-Powered Decision Systems

• Experience deploying and managing LLMs on local or on-premises environments.
• Experience with agent orchestration frameworks.
• Knowledge of AI infrastructure optimization.
• Understanding of prompt engineering techniques.
• Familiarity with vector databases and semantic search.
• Experience integrating enterprise AI solutions into production environments.
• Exposure to cloud-based AI services and MLOps practices.

The ideal candidate combines:

• Strong Python Development Skills
• Machine Learning Engineering Experience
• LLM & RAG Implementation Experience
• NLP Expertise
• API Integration Capabilities
• Agentic AI Knowledge
• Production AI Deployment Experience

For AI Engineer positions, employers place strong emphasis on practical AI implementations. Highlight projects involving LLMs, RAG architectures, AI agents, NLP solutions, model deployments, and business outcomes achieved through AI. Demonstrating experience with production-grade AI systems, scalable deployments, and measurable improvements in automation, accuracy, or customer experience will significantly strengthen your application.