Ai Engineer
ULA | Ultimate Learning Academy Co. · Riyadh Region
Apply & track with Apply EdgeRole OverviewWe are looking for a highly skilled Senior AI Engineer to design, develop, and deploy advanced AI and machine learning solutions. The successful candidate will work closely with data scientists, software engineers, product teams, and business stakeholders to transform complex business requirements into scalable AI solutions.Key ResponsibilitiesDesign, develop, and deploy AI/ML models for real-world business applications.Develop and optimize Generative AI, LLM, NLP, and machine learning solutions.Build and maintain production-ready AI pipelines and APIs.Work with frameworks such as PyTorch, TensorFlow, Hugging Face, and LangChain.Develop RAG, agentic AI, prompt engineering, and LLM evaluation solutions.Integrate AI models with enterprise applications, databases, and cloud platforms.Optimize models for performance, scalability, reliability, and cost.Establish best practices for AI development, testing, monitoring, and deployment.Mentor junior and mid-level AI engineers and contribute to technical decisions.Collaborate with cross-functional teams to identify and deliver high-impact AI use cases.Stay current with emerging AI technologies, research, and industry best practices.Required QualificationsBachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.5+ years of experience in AI/ML engineering or a related technical field.Strong proficiency in Python and software engineering principles.Hands-on experience building and deploying ML/AI models in production.Strong understanding of machine learning and deep learning concepts.Experience with LLMs, Generative AI, RAG, embeddings, vector databases, and AI agents.Experience with cloud platforms such as AWS, Azure, or Google Cloud.Strong knowledge of APIs, microservices, Git, CI/CD, and containerization technologies such as Docker/Kubernetes.Strong analytical, problem-solving, and communication skills.Preferred QualificationsExperience with MLOps/LLMOps and model monitoring.Experience with enterprise AI architecture and scalable systems.Knowledge of responsible AI, model governance, security, and data privacy.Experience with Azure OpenAI, OpenAI APIs, or other foundation-model platforms.Publications, open-source contributions, or demonstrated AI projects are a plus.