# NLP Engineer - Arabic Language Focus — Devsinc

Canonical: https://jobxdubai.com/jobs/47f8159d-nlp-engineer-arabic-language-focus
Location: Riyadh, Saudi Arabia
Type: full_time · Level: mid
Monthly salary: AED 19,600 to 34,300 per month (estimated, not employer-stated) (UAE salaries are tax-free)
Posted: 2026-06-09
Apply: https://jobs.workable.com/view/9Ts2Scz9fn4L7AzZXitbL3/nlp-engineer---arabic-language-focus-in-riyadh-at-devsinc

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## Description

We are seeking an experienced NLP Engineer with strong expertise in Arabic Language Processing and Large Language Models (LLMs) to design, develop, and deploy intelligent AI solutions for Arabic and multilingual applications. The role involves building advanced NLP systems for chatbots, virtual assistants, intelligent search, document processing, and other AI-driven digital solutions.

The ideal candidate will have hands-on experience in developing production-grade NLP models, implementing Retrieval-Augmented Generation (RAG) architectures, and deploying scalable AI services in cloud environments.

Benefits
- Medical Inpatient & Outpatient Facilities
- Paid Overtime
- Engaging Company Activities
- Sports Allowance

## Requirements

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field. 
- 3–6 years of experience in NLP, Machine Learning, or AI Engineering. 
- Strong experience working with Arabic language NLP solutions. 
- Proficiency in Python and modern NLP/ML frameworks. 
Hands-on experience with:
- Transformers and Large Language Models (LLMs)
- Embeddings and Vector Search
- Tokenization
- Text Classification
- Named Entity Recognition (NER)
- Sentiment Analysis
- Text Summarization
- Retrieval-Augmented Generation (RAG)
- Proficiency in Python.
- Experience with Hugging Face, spaCy, and FastAPI.
- Experience implementing MLOps practices, including model deployment, monitoring, and lifecycle management.
- Experience deploying AI solutions on cloud platforms such as AWS, Azure, or GCP.
- Strong understanding of scalable AI architectures and production environments

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