Senior AI Engineer Consultant

Role overview

Key responsibilities

• Build enterprise-grade LLM applications using RAG, tool calling, structured generation, prompt engineering, and agentic workflows.
• Implement and optimize LLM inference, including model serving, quantization, caching, batching, and GPU utilization where relevant.
• Develop LLM evaluation frameworks for accuracy, relevance, hallucination, safety, latency, and cost.
• Assess open-source and commercial foundation models for specific use cases.
• Build reusable components such as knowledge retrieval, model gateways, evaluation pipelines, and agent orchestration.
• Deploy AI/ML workloads across cloud, on-premise, and hybrid environments.
• Implement model versioning, experiment tracking, monitoring, logging, and automated deployment pipelines.
• Optimize AI workloads for scalability, reliability, latency, and cost; troubleshoot production AI systems and improve performance.

Qualifications and experience

• Bachelor’s degree in Computer Science, Software Engineering, Computer Information Systems, AI, Data, or a related stated discipline.
• 7+ years of experience in AI Engineering.
• Experience working with clients, government, consulting, GCC, or the Saudi market.
• Experience deploying AI/ML workloads to cloud, on-premise, and hybrid environments.
• Experience with Docker, Kubernetes, GPU infrastructure, and cloud AI/ML services.
• Experience implementing model versioning, experiment tracking, monitoring, logging, and automated deployment pipelines.
• Ability to optimize workloads and troubleshoot production AI systems.

Professional and language skills

• Strong communication, presentation, stakeholder management, interpersonal, analytical, and problem-solving skills.
• Consulting and client-facing mindset; ability to work independently and collaboratively with strong organizational and time-management skills.
• Arabic speakers and English are listed under language requirements.