AI Engineer - Riyadh, KSA

DeepSource; Saudi Arabia; On-site; SAR 200,000 - 300,000; Full time

Job summary

A dynamic tech company in Saudi Arabia is seeking an AI Engineer to design and integrate AI-driven features into digital products. The role involves identifying opportunities for AI integration, building machine learning models, and collaborating with teams to ensure quality and compliance. Candidates should possess strong skills in AI/ML technologies, data preparation, and model optimization. This position is critical for driving innovative solutions and enhancing user experiences.

Qualifications

• Experience with integrating AI/ML into digital products.
• Proficient in building and deploying machine learning models.
• Familiar with data preparation and pipeline building.

Responsibilities

• Identify opportunities to integrate AI/ML into products.
• Build and deploy machine learning models using modern frameworks.
• Work with teams to clean and prepare datasets.

Skills

AI/ML integration

Machine learning model building

Data engineering

Collaboration with product teams

Optimizing model performance

Security and compliance awareness

Prototyping and POCs

Tools

TensorFlow

PyTorch

Scikit-learn

Job description

We are seeking a skilled AI Engineer to design, develop, and integrate AI-powered features into the company’s digital products. The role focuses on turning business needs into AI-driven functionalities and ensuring scalable, secure, and high-quality AI implementations.

Key Responsibilities

AI Feature Development

• Identify opportunities to integrate AI/ML into digital products (recommendation engines, automation, NLP, predictive analytics, chatbots, etc.).
• Build and deploy machine learning models using modern frameworks (TensorFlow, PyTorch, Scikit-learn).
• Develop AI microservices/APIs to integrate with existing systems.

Product Integration

• Work closely with product managers, designers, and developers to translate features into technical AI solutions.
• Optimize AI model performance, user experience, and cost efficiency.
• Ensure seamless integration into web/mobile/cloud platforms.

Data Engineering & Preparation

• Work with teams to clean, structure, and prepare datasets.
• Build data pipelines for training, testing, and monitoring AI models.
• Ensure data quality, privacy, and governance compliance.

AI Strategy & Innovation

• Advise leadership on AI opportunities and emerging technologies.
• Build prototypes, POCs, and MVPs for new AI features.
• Introduce best practices for model lifecycle management (MLOps).

Quality, Security, and Compliance

• Ensure AI models meet accuracy, fairness, explainability, and security requirements.
• Implement monitoring and retraining mechanisms for AI models.
• Document technical solutions, workflows, and architecture.