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Key Responsibilities: Build enterprise-grade LLM applications using techniques such as 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 covering accuracy, relevance, hallucination, safety, latency, and cost. Work with open-source and commercial foundation models and assess their suitability for specific use cases. Build reusable components for enterprise AI applications, including knowledge retrieval, model gateways, evaluation pipelines, and agent orchestration. Required Qualifications & Skills: Deploy AI/ML workloads to cloud, on-premise, and hybrid environments. Work with Docker, Kubernetes, GPU infrastructure, and cloud AI/ML services. 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 continuously improve system performance Education: Bachelor's degree in computer science, Software Engineering, Computer Information Systems (CIS), AI and Data. Professional Experience 7+ years of experience in AI Engineering. Experience working with [Clients / Government / Consulting / GCC / Saudi market]. Soft Skills Strong communication and presentation skills. Strong stakeholder management and interpersonal skills. Analytical and problem-solving capabilities. Consulting and client-facing mindset. Ability to work independently and collaboratively. Strong organizational and time-management skills. Language Requirements Arabic Speakers English Location & Employment Details Location: Riyadh Employment Type: Full-time.
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