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Senior AI Engineer (Arabic Speaker)

Datamatics Global Services Ltd
الرياض, KSA
fulltime
Senior
Yesterday
Machine LearningDeep LearningPythonTensorFlowPyTorchData Science
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Senior Ai Engineer (Arabic Speaker)

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Employment Type:** Full-Time And Contract

**Language Requirement:** Native or Fluent Arabic Speaker (Mandatory)

About The Role

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We are seeking a highly skilled **Senior AI Engineer (Arabic Speaker)** to join our growing AI and Data Science team in Riyadh.

The ideal candidate will have strong expertise in **Artificial Intelligence, Generative AI, Machine Learning Operations (MLOps), and Cloud-based AI Platforms**, with proven experience in designing, developing, deploying, and managing enterprise-grade AI solutions.

The successful candidate will play a key role in building scalable AI systems, implementing GenAI applications, operationalizing machine learning models, and collaborating with business stakeholders to deliver innovative AI-driven solutions that create measurable business impact.

Key Responsibilities

------------------------

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.

Required Technical Skills

-----------------------------

Artificial Intelligence & Machine Learning

  • Machine Learning
  • Deep Learning

• Natural Language Processing (NLP)

  • Predictive Analytics

• 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

• Google Cloud Platform (GCP)

  • Oracle Cloud Infrastructure (OCI) – Preferred

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

  • ------------------
  • Bachelor's Degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related discipline.
  • Master's Degree in AI, Machine Learning, Data Science, or related field is highly preferred.

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.

Preferred Certifications

----------------------------

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.
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