Senior AI Engineer (Arabic Speaker)
Tasks
- Automate model deployment with CI/CD
- Build AI-ready data pipelines
- Build predictive analytics NLP recommendation systems
- Build prompt engineering frameworks optimize prompts
- Deploy AI ML workloads on cloud platforms
- Design and implement end-to-end MLOps pipelines
- Design and implement enterprise GenAI solutions
- Design develop train and deploy machine learning models
- Develop generative AI applications using large language models
- Ensure data quality security privacy compliance
- Establish AI governance model versioning reproducibility compliance
- Evaluate and benchmark AI models
- Fine tune foundation models implement RAG architectures
- Implement AI agents and autonomous workflows
- Implement vector databases semantic search
- Integrate AI solutions with enterprise APIs databases and apps
- Manage containerized AI environments with Docker and Kubernetes
- Monitor model performance drift detection retraining
- Present AI architectures and project outcomes
- Translate business requirements into technical AI solutions
Perks/Benefits
Skills/Tech-stack
AI Agents | AWS | Airflow | Bash | CI/CD | Cloud infrastructure | Cloud platform | Deep learning | Docker | Feature Stores | Generative AI | Git | GitHub Actions | Google Cloud | Google Cloud Platform | Infrastructure as Code | Jenkins | Kubeflow | Kubernetes | Language Models | Language Processing | Large Language Models | MLOps | MLflow | Machine Learning | Microsoft Azure | Model Governance | Model Monitoring | Model Registry | Natural Language | Natural Language Processing | Oracle Cloud | Oracle Cloud Infrastructure | Predictive Analytics | Prompt engineering | Python | Retrieval-Augmented Generation | SQL | Semantic Search | Terraform | Vector Databases | “as-code”
Education
Roles
Regions
Countries
States
Cities
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