Senior AI Engineer (Arabic Speaker)

Overview

Ai & Machine Learning Development

• Design, develop, train, and deploy machine learning and deep learning models for enterprise use cases.
• Build and optimize predictive analytics, NLP, recommendation systems, and intelligent automation solutions.
• Develop AI-powered applications leveraging Large Language Models (LLMs) and Generative AI technologies.
• Fine-tune foundation models and implement Retrieval-Augmented Generation (RAG) architectures.
• Evaluate and benchmark AI models to ensure performance, scalability, and reliability.

Generative Ai Engineering

• Design and implement enterprise GenAI solutions using OpenAI, Azure OpenAI, Claude, Gemini, Llama, Mistral, and other LLM platforms.
• Develop conversational AI solutions, intelligent assistants, and knowledge management systems.
• Build prompt engineering frameworks and optimize prompts for business use cases.
• Implement vector databases and semantic search solutions.
• Develop AI agents and autonomous workflows using modern AI orchestration frameworks.

Mlops & Ai Operations

• Design and implement end-to-end MLOps pipelines for model training, deployment, monitoring, and lifecycle management.
• Automate model deployment using CI/CD pipelines and infrastructure-as-code practices.
• Monitor model performance, drift detection, retraining strategies, and operational KPIs.
• Establish AI governance, model versioning, reproducibility, and compliance standards.
• Implement scalable AI platforms supporting multiple business units.

Cloud & Platform Engineering

• Deploy AI/ML workloads on cloud platforms such as Azure, AWS, GCP, or OCI.
• Manage containerized AI environments using Docker and Kubernetes.
• Design scalable AI infrastructure supporting high-volume enterprise workloads.
• Optimize cloud resources, performance, and operational costs.

Data Engineering & Integration

• Collaborate with data engineering teams to build AI-ready data pipelines.
• Integrate AI solutions with enterprise applications, APIs, databases, and business platforms.
• Ensure data quality, security, privacy, and compliance with organizational standards.

Stakeholder Management

• Engage with business stakeholders to identify AI opportunities and translate business requirements into technical solutions.
• Present AI solution architectures, recommendations, and project outcomes to technical and non-technical audiences.
• Mentor junior AI engineers, data scientists, and platform engineers.

Artificial Intelligence & Machine Learning

• Machine Learning
• Deep Learning

• Natural Language Processing (NLP)

• Predictive Analytics

• Reinforcement Learning (preferred)

• Generative AI

• Retrieval-Augmented Generation (RAG)

• Prompt Engineering

• AI Agents & Multi-Agent Systems

• Fine-Tuning and Model Optimization

Mlops

• MLflow
• Kubeflow
• Airflow

• Model Monitoring & Observability

• CI/CD for ML
• Feature Stores
• Model Registry
• Experiment Tracking
• Model Governance

Cloud Platforms

• Microsoft Azure
• AWS

Containers & Devops

• Docker
• Kubernetes
• Git
• GitHub Actions
• Jenkins
• Terraform
• Infrastructure as Code

Programming Languages

• Python (Mandatory)
• SQL
• Bash/Shell Scripting
• Java or C# (Preferred)

Qualifications

Experience Requirements

• 6 – 8 years of experience in AI/ML Engineering, Data Science, or AI Platform Engineering.
• Minimum 3+ years of hands-on experience implementing Generative AI solutions.
• Proven experience building and operationalizing machine learning models in production environments.
• Strong experience implementing enterprise MLOps frameworks and practices.
• Experience working with cloud-native AI services and modern AI platforms.

Soft Skills

• Strong analytical and problem-solving skills.
• Excellent communication and stakeholder management abilities.
• Ability to work effectively in cross-functional and multicultural environments.
• Strong ownership, accountability, and leadership mindset.
• Passion for innovation and continuous learning.
• Ability to communicate fluently in both Arabic and English.

Mandatory Requirements

• Native or Fluent Arabic Speaker.
• 6 – 8 years of relevant AI/ML engineering experience.
• Hands-on expertise in Generative AI and MLOps.
• Strong Python programming skills.
• Experience deploying AI solutions in enterprise production environments.
• Willingness to work onsite in Riyadh, Saudi Arabia.