LLM Engineer

Description

Design, develop, and deploy Arabic-first large language model (LLM) solutions to support AI-driven products and client projects, ensuring high-quality Arabic language understanding, generation, and contextual accuracy across enterprises.

Key Responsibilities

1. LLM Development & NLP (Core)
   Design and fine-tune LLMs for Arabic language tasks:
   
   • Text generation, classification, summarization
   • Arabic grammar correction, dialect handling
   • Build and optimize RAG pipelines
   • Develop prompt engineering strategies for Arabic and English contexts
2. Data & Arabic Language Engineering
   Build and curate Arabic datasets.
   Handle:
   
   • Dialects (Gulf, MSA, etc.)
   • Data cleaning, normalization
   Define evaluation benchmarks for Arabic LLM quality.
3. AI System Architecture
   Develop LLM-powered systems using:
   
   • LangChain / LangGraph / Llama / OpenAI APIs
   • Vector databases (ChromaDB, FAISS, etc.)
   Integrate LLMs into:
   
   • APIs
   • Enterprise systems
   • AI agents / copilots
4. Production & MLOps
   Deploy scalable AI systems using:
   
   • Docker, Kubernetes
   • Cloud platforms (Azure, AWS, GCP)
   Optimize:
   
   • Latency
   • Cost
   • Throughput
5. Cross-functional Collaboration
   Work with:
   
   • PMs (scope, delivery, timelines)
   • BAs (requirements translation – AI logic)
   • QA (model validation & test cases)
   Support client demos and AI solution design.
6. Governance Alignment (Critical for Nabeh)
   Ensure:
   
   • AI outputs align with client expectations
   • Traceability (data – model – output)
   Support:
   
   • BRD validation (AI feasibility)
   • UAT and acceptance criteria

Requirements

Required Skills

Technical
Strong in:

• Python (PyTorch / TensorFlow)
• NLP & LLMs (Transformers, RAG)

Experience with:

• LangChain / LLM frameworks
• Vector databases
• Prompt engineering

Arabic AI (Mandatory):

• Native or fluent Arabic
• Experience in Arabic NLP
• Dataset preparation for Arabic
• Handling dialects

Engineering & Deployment:

• APIs (FastAPI / Flask)
• Microservices architecture
• Docker, Kubernetes
• CI/CD pipelines

Language Requirements

• Arabic: Native / Fluent (Mandatory)
• English: Professional (Mandatory)

Preferred Qualifications

• MSc or higher in AI / Data Science / NLP
• Experience in Arabic LLMs (high priority)
• Government or enterprise AI projects
• Certifications:
  
  • Azure AI / ML
  • MLOps / Cloud certifications