At Intella, we're building Arabic-native AI technologies that power the future of voice and language intelligence across the MENA region. Our work spans advanced foundation models, multi-agent systems, and production-grade AI pipelines designed for real-world enterprise use cases. If you're passionate about applied AI — from model research to scalable deployment — and you want to solve complex challenges in speech, text, and multimodal Arabic AI, we'd love to meet you.
Role Overview
As an AI Engineer, you'll join our cross-functional AI research and engineering team to design, build, and scale innovative AI systems. You'll work at the intersection of applied research, software engineering, and MLOps — bridging cutting-edge models with real-world applications.
Key Responsibilities
- Research & Innovation: Explore and implement state-of-the-art techniques using foundation models, prompt engineering, retrieval-augmented generation (RAG), graph-based reasoning, and multi-agent architectures.
- Model Training & Evaluation: Fine-tune foundation and domain-specific models, and rigorously evaluate performance on accuracy, relevance, bias, hallucination, and latency through offline and online experiments.
- Prototyping & Deployment: Build rapid prototypes, contribute to production AI systems, debug and optimize code, and collaborate with MLOps/AIOps for scalable deployment.
- Data & Insights: Use structured and unstructured data to identify gaps in AI quality, uncover insights, and deliver high-impact PoCs that demonstrate measurable value.
- Documentation & Communication: Maintain clear experiment logs, reproducible research pipelines, and concise documentation for internal and external stakeholders.
- Cross-Functional Collaboration: Work with product, backend, and data teams to integrate AI capabilities into Intella's ecosystem and client-facing applications.
- Continuous Learning: Stay up to date on LLM research, open-source trends, and applied AI technologies.
Required Qualifications
- Strong understanding of LLM architectures, deep learning, and multi-agent systems.
- Hands-on experience in model fine-tuning, evaluation, and deployment.
- Proficiency in Python
- Knowledge of classical ML (tree-based models, optimization, feature engineering) and modern DL (Transformers, diffusion, multimodal architectures).
- Strong understanding of APIs, data flows, and service-oriented architectures.
- Demonstrated ability to communicate complex technical ideas to diverse audiences.
- Track record of taking projects from 0→1 and improving existing systems in production environments.
- Bachelor's, Master's, or Ph.D. in Computer Science, AI, or related field (or equivalent experience).
Nice-to-Have
- Experience building Arabic language models and systems.
- Experience in addressing scalability and latency challenges.
- Familiarity with Speech language systems.
- Prior work in generative AI for enterprise or applied conversational systems.
- Proficiency in one of: Golang or TypeScript (React, Next.js).
