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 (careers@eyouthlearning.com) & mention the job title in the subject Show more