AI Engineer

Key Responsibilities

• Design, develop, train, and deploy AI and Machine Learning models for business applications.
• Build and optimize data pipelines for data collection, preprocessing, and feature engineering.
• Develop AI-powered applications using NLP, Computer Vision, Predictive Analytics, and Generative AI technologies.
• Integrate AI solutions with enterprise applications, APIs, and cloud platforms.
• Evaluate, monitor, and improve the performance and accuracy of AI models.
• Collaborate with data scientists, software developers, and business stakeholders to translate business requirements into AI solutions.
• Perform model testing, validation, deployment, and ongoing maintenance.
• Work with structured and unstructured datasets to derive actionable insights.
• Prepare technical documentation, model reports, and deployment guidelines.
• Stay updated with the latest advancements in Artificial Intelligence, Machine Learning, and Generative AI technologies.

Required Qualifications

• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field.
• 3–4 years of hands-on experience in AI/ML solution development and deployment.
• Strong proficiency in Python and AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, Keras, or similar.
• Experience with Large Language Models (LLMs), Generative AI, Natural Language Processing (NLP), or Computer Vision.
• Strong knowledge of SQL and NoSQL databases.
• Experience with REST APIs, microservices, and cloud platforms (Azure, AWS, or Google Cloud).
• Familiarity with MLOps, model deployment, Docker, and Git version control.
• Strong analytical, problem-solving, and debugging skills.
• Excellent communication and teamwork abilities.
• Arabic speaking is mandatory. English communication skills are also required.

Preferred Skills

• Experience with Azure AI Services, Azure OpenAI, AWS SageMaker, or Google Vertex AI.
• Knowledge of RAG (Retrieval-Augmented Generation), vector databases, and prompt engineering.
• Experience with Power BI or Tableau for AI-driven analytics.
• Familiarity with DevOps and CI/CD pipelines.
• AI-related certifications are an added advantage.