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 01 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).
