AI Engineer

Sundus

Abu Dhabi

On-site

AED 90,000 - 130,000

Full time

14 days+
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Job summary

Sundus is seeking an AI Engineer to develop, test, and deploy AI/ML and Generative AI solutions, including LLM-based applications, RAG pipelines, and Agentic workflows. The role supports on-premise deployment for secure enterprise delivery.

The candidate should have 2+ years in AI/ML, a Bachelor’s in CS/AI/Data Science, and strong Python skills to design robust, scalable AI systems deployed in enterprise environments.

Qualifications

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

Responsibilities

  • Develop, test, and deploy AI/ML and Generative AI solutions.
  • Build LLM-based applications and RAG pipelines.
  • Implement agentic workflows and on-prem LLM deployment.
  • Ensure secure enterprise delivery of AI solutions.

Skills

Python
ML/DL concepts
NLP basics

Education

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

Tools

Git/version control
REST APIs

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.

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