Mid-Level AI Engineer

Role Overview We are looking for a Mid-Level AI Engineer with hands-on experience in Natural Language Processing, LLM-based applications, RAG, and speech/voice technologies. The engineer will help design, build, evaluate, and deploy AI-powered solutions for education, automation, content operations, and user engagement.

This role is important for the Fahem roadmap and the wider AI layer across the eyouth learning journey,

including in-course tutoring, transcription, quiz generation, Arabic AI capabilities, and trainer evaluation.

Key Responsibilities

• Design and develop AI applications using LLMs, NLP techniques, and production-ready Python services.
• Build conversational AI systems, chatbots, AI assistants, and education-focused copilots.
• Develop and optimize voice AI pipelines, including Speech-to-Text, Text-to-Speech, and voice interaction

flows.

• Implement Retrieval-Augmented Generation (RAG) architectures using embeddings, vector databases,

and approved knowledge sources.

• Fine-tune, evaluate, and monitor language models for production use cases where appropriate.
• Build REST APIs and scalable backend services for AI-powered features.
• Integrate OpenAI APIs, Hugging Face models, LangChain/LlamaIndex, and other AI services.
• Work on Arabic NLP use cases, including Arabic content understanding, dialect handling, and learner

support.

• Collaborate with product, backend, frontend, data, and training teams to deliver AI-driven features.
• Monitor AI quality, latency, cost, hallucination risk, and reliability in production.

Requirements And Qualifications

• 2-3 years of hands-on experience in AI, ML, NLP, or LLM application development.
• Strong Python experience and ability to build clean, maintainable services.
• Hands-on experience with NLP and LLM frameworks.
• Knowledge of Arabic NLP and Arabic language use cases.
• Experience with OpenAI APIs, LangChain or LlamaIndex, and Hugging Face Transformers.
• Good understanding of prompt engineering, RAG systems, embeddings, and retrieval evaluation.
• Experience with vector databases such as Pinecone, Weaviate, ChromaDB, or similar.
• Familiarity with REST APIs, backend development, and Git-based collaboration.
• Practical experience with Voice AI, including STT, TTS, or voice interaction workflows.
• Experience deploying AI systems on AWS, Azure, or GCP.
• Experience fine-tuning or evaluating open-source LLMs.
• Experience with AI observability, model evaluation, guardrails, and cost optimization.
• Experience in EdTech, learning platforms, tutoring systems, or Arabic content products.

If you meet the above requirements and are looking for a challenging and rewarding opportunity to join our team, please submit your resume to ([email protected]) & mention the job title in the subject