AI Engineer

Sundus Gulf; Abu Dhabi; On-site; AED 180,000 - 320,000; Full time

Job summary

Sundus Gulf in Abu Dhabi seeks an AI Engineer to design, test, and deploy AI/ML and Generative AI solutions, including LLM-based applications, RAG pipelines, and agentic workflows. You will enable on-premise deployment for secure enterprise AI.

The ideal candidate has 2+ years in AI/ML, strong Python, and hands-on experience with ML frameworks, NLP basics, and API integration. You will collaborate with cross-functional teams to deliver scalable AI capabilities.

Qualifications

• Bachelor's degree in Computer Science, AI, Data Science, or related field.
• 2+ years of experience in AI/ML development.
• Strong programming skills in Python.
• Hands-on experience with ML frameworks (Scikit-learn, PyTorch, or TensorFlow).
• Familiarity with REST APIs and integration concepts.
• Experience with Git/version control.

Skills

2+ years AI/ML development

Python programming

ML frameworks (Scikit-learn, PyTorch,或

Education

Bachelor's degree in Computer Science, AI, Data Science, or related field

Job description

Job Title

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

Job Code

JPC 6310

Experience

2+ years of experience in AI/ML development.

Education

Bachelor's degree in Computer Science, AI, Data Science, or related field.

Language Skills

English

Role Purpose

The AI Engineer is responsible for developing, testing, and deploying AI/ML and
Generative AI solutions, including LLM-based applications, RAG pipelines, and
Agentic workflows. This role also includes the ability to deploy and run LLMs on
local/on-premise servers, supporting secure and efficient AI solution delivery in
enterprise environments.

Required Skills & Qualifications

• Bachelor's degree in Computer Science, AI, Data Science, or related field.
• 2+ years of experience in AI/ML development.
• Strong programming skills in Python.

Hands-on experience with:

• Machine learning frameworks (Scikit-learn, PyTorch, or TensorFlow)
• Basic NLP concepts
• Understanding of ML model lifecycle (training, evaluation, deployment).
• Familiarity with REST APIs and integration concepts.
• Experience with Git/version control.