Senior AI Engineer (Arabic Speaker)

Senior AI Engineer (Arabic Speaker)Location: Riyadh, Saudi ArabiaExperience: 6–8 YearsEmployment Type: Full-Time / ContractLanguage Requirement: Native or Fluent Arabic Speaker (Mandatory)About the RoleWe are seeking a highly skilled Senior AI Engineer (Arabic Speaker) to join our growing AI and Data Science team in Riyadh. The ideal candidate will have strong expertise in Artificial Intelligence, Generative AI, Machine Learning Operations (MLOps), and Cloud-based AI Platforms, with proven experience in designing, developing, deploying, and managing enterprise-grade AI solutions.The successful candidate will play a key role in building scalable AI systems, implementing GenAI applications, operationalizing machine learning models, and collaborating with business stakeholders to deliver innovative AI-driven solutions that create measurable business impact.Key ResponsibilitiesAI & Machine Learning DevelopmentDesign, develop, train, and deploy machine learning and deep learning models for enterprise use casesBuild and optimize predictive analytics, NLP, recommendation systems, and intelligent automation solutionsDevelop AI-powered applications leveraging Large Language Models (LLMs) and Generative AI technologiesFine-tune foundation models and implement Retrieval-Augmented Generation (RAG) architecturesEvaluate and benchmark AI models to ensure performance, scalability, and reliabilityGenerative AI EngineeringDesign and implement enterprise GenAI solutions using OpenAI, Azure OpenAI, Claude, Gemini, Llama, Mistral, and other LLM platformsDevelop conversational AI solutions, intelligent assistants, and knowledge management systemsBuild prompt engineering frameworks and optimize prompts for business use casesImplement vector databases and semantic search solutionsDevelop AI agents and autonomous workflows using modern AI orchestration frameworksMLOps & AI OperationsDesign and implement end-to-end MLOps pipelines for model training, deployment, monitoring, and lifecycle managementAutomate model deployment using CI/CD pipelines and infrastructure-as-code practicesMonitor model performance, drift detection, retraining strategies, and operational KPIsEstablish AI governance, model versioning, reproducibility, and compliance standardsImplement scalable AI platforms supporting multiple business unitsCloud & Platform EngineeringDeploy AI/ML workloads on cloud platforms such as Azure, AWS, GCP, or OCIManage containerized AI environments using Docker and KubernetesDesign scalable AI infrastructure supporting high-volume enterprise workloadsOptimize cloud resources, performance, and operational costsData Engineering & IntegrationCollaborate with data engineering teams to build AI-ready data pipelinesIntegrate AI solutions with enterprise applications, APIs, databases, and business platformsEnsure data quality, security, privacy, and compliance with organizational standardsStakeholder ManagementEngage with business stakeholders to identify AI opportunities and translate business requirements into technical solutionsPresent AI solution architectures, recommendations, and project outcomes to technical and non-technical audiencesMentor junior AI engineers, data scientists, and platform engineersRequired Technical SkillsArtificial Intelligence & Machine LearningMachine LearningDeep LearningNatural Language Processing (NLP)Predictive AnalyticsComputer Vision (preferred)Reinforcement Learning (preferred)Generative AILarge Language Models (LLMs)Retrieval-Augmented Generation (RAG)Prompt EngineeringAI Agents & Multi-Agent SystemsFine-Tuning and Model OptimizationVector Databases (Pinecone, Weaviate, ChromaDB, FAISS)LangChain, LlamaIndex, Semantic Kernel, CrewAI, AutoGenMLOpsMLflowKubeflowAirflowModel Monitoring & ObservabilityCI/CD for MLFeature StoresModel RegistryExperiment TrackingModel GovernanceCloud PlatformsMicrosoft AzureAWSGoogle Cloud Platform (GCP)Oracle Cloud Infrastructure (OCI) – PreferredContainers & DevOpsDockerKubernetesGitGitHub ActionsJenkinsTerraformInfrastructure as CodeProgramming LanguagesPython (Mandatory)SQLBash/Shell ScriptingJava or C# (Preferred)QualificationsBachelor's Degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related disciplineMaster's Degree in AI, Machine Learning, Data Science, or related field is highly preferredExperience Requirements6–8 years of experience in AI/ML Engineering, Data Science, or AI Platform EngineeringMinimum 3+ years of hands-on experience implementing Generative AI solutionsProven experience building and operationalizing machine learning models in production environmentsStrong experience implementing enterprise MLOps frameworks and practicesExperience working with cloud-native AI services and modern AI platformsPreferred CertificationsMicrosoft Azure AI Engineer AssociateAWS Machine Learning SpecialtyGoogle Professional Machine Learning EngineerOCI AI Foundations AssociateKubernetes Certifications (CKA/CKAD)Databricks Machine Learning ProfessionalSoft SkillsStrong analytical and problem-solving skillsExcellent communication and stakeholder management abilitiesAbility to work effectively in cross-functional and multicultural environmentsStrong ownership, accountability, and leadership mindsetPassion for innovation and continuous learningAbility to communicate fluently in both Arabic and EnglishMandatory RequirementsNative or Fluent Arabic Speaker6–8 years of relevant AI/ML engineering experienceHands-on expertise in Generative AI and MLOpsStrong Python programming skillsExperience deploying AI solutions in enterprise production environmentsWillingness to work onsite in Riyadh, Saudi Arabia