Technical Lead Enterprise AI

Lead the technical architecture and solution design for enterprise AI initiatives Mentor and manage a team of AI/ML engineers to deliver high-quality solutions Engage directly with customers to gather requirements, present designs, and ensure successful delivery Oversee the fine-tuning, deployment, and performance optimization of large language models Collaborate with cross-functional teams including data engineering, DevOps, and product management Ensure best practices for security, scalability, and maintainability on Azure cloud Monitor project progress, manage risks, and drive continuous improvement Required

Qualifications

10 12 years of experience architecting and delivering enterprise AI solutions Deep technical expertise in AI/ML, large language models, and natural language processing Proven solution design skills with complex, large-scale systems Hands-on experience with Microsoft Azure AI services (e.g., Cognitive Services, Azure ML) Strong customer engagement and communication skills to interact with stakeholders at all levels Demonstrated ability to lead and mentor technical teams

Qualifications

10 12 years of experience architecting and delivering enterprise AI solutions Deep technical expertise in AI/ML, large language models, and natural language processing Proven solution design skills with complex, large-scale systems Hands-on experience with Microsoft Azure AI services (e.g., Cognitive Services, Azure ML) Strong customer engagement and communication skills to interact with stakeholders at all levels Demonstrated ability to lead and mentor technical teams Bachelor s degree in Computer Science, Engineering, or a related field

Preferred Qualifications

Master s or PhD in AI, Machine Learning, Data Science, or related discipline Microsoft Azure certifications (e.g., Azure AI Engineer Associate) Experience with MLOps frameworks and CI/CD pipelines Background in regulated industries such as finance, healthcare, or government Familiarity with hybrid cloud and on-premises deployment models in the Saudi market