Senior AI Engineer (Arabic Speaker)

Role overview

We are looking for an experienced Senior AI Engineer to join an AI and Data Science team in Riyadh. This position is focused on building enterprise-ready artificial intelligence solutions, including generative AI products, machine learning operations, and scalable cloud-based platforms.

The role calls for someone who can turn business needs into technical AI solutions, deliver production-grade systems, and work closely with stakeholders across technical and non-technical teams. The ideal candidate will also help mentor other engineers and contribute to the maturity of AI practices across the organization.

Location and employment

Location: Riyadh, Saudi Arabia

Employment type: Full-time / Contract

Work mode: Onsite

Experience required: 6–8 years

Language requirement: Native or fluent Arabic speaker is mandatory. Strong communication in both Arabic and English is expected.

Key responsibilities

• Build, train, fine-tune, and deploy machine learning and deep learning models for enterprise scenarios.
• Create intelligent solutions for predictive analytics, NLP, recommendation engines, and automation use cases.
• Develop applications powered by large language models and generative AI tools.
• Implement retrieval-augmented generation approaches and optimize foundation models for business needs.
• Test and compare model performance to make sure solutions are reliable, scalable, and efficient.
• Design enterprise GenAI solutions using platforms such as OpenAI, Azure OpenAI, Claude, Gemini, Llama, Mistral, and similar LLM ecosystems.
• Build conversational AI experiences, smart assistants, and knowledge management systems.
• Create prompt engineering methods and improve prompts for real business workflows.
• Set up vector databases and semantic search capabilities.
• Develop AI agents and autonomous workflows using modern orchestration frameworks.
• Design and run end-to-end MLOps pipelines covering training, deployment, monitoring, and lifecycle management.
• Automate model release processes with CI/CD and infrastructure-as-code practices.
• Track model drift, operational metrics, and retraining triggers, while maintaining governance and reproducibility standards.
• Deploy AI and ML workloads on cloud platforms such as Azure, AWS, GCP, or OCI.
• Manage Docker and Kubernetes-based containerized environments for AI systems.
• Work with data teams to create AI-ready pipelines and integrate solutions with APIs, databases, and enterprise applications.
• Maintain data quality, privacy, security, and compliance across integrations.
• Partner with business stakeholders to identify opportunities and convert requirements into technical designs.
• Present architectures, recommendations, and results to both technical and non-technical audiences.
• Guide and mentor junior AI engineers, data scientists, and platform engineers.

Required skills and experience

• Strong experience in machine learning, deep learning, and natural language processing.
• Hands-on knowledge of predictive analytics, with computer vision and reinforcement learning as preferred areas.
• Practical expertise in generative AI, large language models, prompt engineering, and model fine-tuning.
• Experience working with retrieval-augmented generation, AI agents, and multi-agent systems.
• Familiarity with vector databases such as Pinecone, Weaviate, ChromaDB, or FAISS.
• Knowledge of orchestration and framework tools such as LangChain, LlamaIndex, Semantic Kernel, CrewAI, or AutoGen.
• Solid MLOps background including MLflow, Kubeflow, Airflow, model monitoring, experiment tracking, model registry, feature stores, and governance.
• Experience with cloud platforms, especially Azure, AWS, GCP, and preferably OCI.
• Working knowledge of Docker, Kubernetes, Git, GitHub Actions, Jenkins, Terraform, and infrastructure as code.
• Strong Python programming ability is required; SQL and Bash/Shell scripting are also expected.
• Java or C# is an added advantage.
• Excellent analytical thinking, communication, stakeholder management, ownership, and leadership skills.
• Ability to work effectively in multicultural and cross-functional teams.
• Fluency in Arabic and English is required.

Qualifications

A bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related area is required. A master's degree in AI, Machine Learning, Data Science, or a similar field is strongly preferred.

Preferred certifications

• Microsoft Azure AI Engineer Associate
• AWS Machine Learning Specialty
• Google Professional Machine Learning Engineer
• OCI AI Foundations Associate
• Kubernetes certifications such as CKA or CKAD
• Databricks Machine Learning Professional

Additional requirements

• Minimum 3+ years of practical experience delivering generative AI solutions.
• Proven track record of building and running machine learning models in production environments.
• Strong exposure to enterprise MLOps frameworks and production AI platforms.
• Experience with cloud-native AI services and modern AI ecosystems.
• Willingness to work onsite in Riyadh, Saudi Arabia.

Who should apply

This role is suitable for professionals with 6–8 years of AI/ML engineering, data science, or AI platform engineering experience who also meet the Arabic language requirement and have strong hands-on expertise in generative AI and MLOps.