AI Engineer

AI Engineer
- MLOps (Job Snapshot)Role: AI Engineer;

Location:
Dubai, United Arab Emirates; Industry: IT and Services; Function: IT-Software Development;

Experience:
4 to 8 years;

Job Type
Full-time;

Salary:
26000-40000. Estimated salary range based on similar jobs in the job city; please confirm the final offer with the employer.
AI Engineer in Dubai, United Arab Emirates is an advanced IT and Services role focused on production-grade AI systems, MLOps frameworks, generative AI integration, scalable model deployment, and secure automation platforms for Majid Al Futtaim Holding. This opportunity is suited to a hands‑on AI and software engineering professional who can connect machine learning experimentation with reliable enterprise systems, reusable deployment pipelines, and business‑ready AI solutions.

Key Responsibilities
Design and build end‑to‑end AI and machine learning solutions covering model training pipelines, deployment environments, monitoring, and performance optimizationDevelop APIs, microservices, and integration layers that embed AI models into business systems, data platforms, enterprise applications, and digital productsCreate and operate MLOps frameworks for model lifecycle management, including CI/CD for machine learning, automated testing, deployment orchestration, and release controlEstablish model governance practices covering versioning, documentation, approval flows, rollback procedures, auditability, and responsible AI controlsWork with infrastructure, cloud, security, and DevOps teams to deliver secure, compliant, scalable, and cost‑optimized environments for AI workloadsIntegrate AI solutions with feature stores, vector databases, data lakes, enterprise data sources, and reusable data pipelinesBuild retrieval‑augmented generation solutions using embeddings, vector search, and large language models for enterprise knowledge and automation use casesSupport AI delivery squads by designing shared components, standardized frameworks, deployment templates, and reusable engineering patternsImprove model performance through inference optimization techniques such as quantization, model compression, distillation, and efficient serving designMaintain strong reliability across deployed AI systems by supporting monitoring, troubleshooting, incident response, and continuous technical improvementIdeal ProfileBachelor's or master's degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, or a related field4 to 8 years of professional experience in software engineering, data engineering, AI engineering, machine learning engineering, or platform developmentAt least 3 years of focused experience in AI/ML engineering, MLOps, production model deployment, or enterprise machine learning infrastructureProven experience delivering production‑grade AI systems and integrating models into real business applications or large‑scale digital platformsHands‑on knowledge of AI and machine learning frameworks such as TensorFlow, PyTorch, scikit‑learn, or similar toolsPractical experience with MLOps and orchestration tools such as MLflow, Kubeflow, Airflow, or related deployment and workflow platformsStrong software engineering ability with Python, API development, microservices, automated testing, and production‑grade coding practicesExperience with model serving, inference optimization, vector databases, feature stores, data lakes, embeddings, and RAG‑based enterprise AI solutionsFamiliarity with DevOps practices, infrastructure as code, Terraform, Helm, containers, Kubernetes, and security standards for AI environments is beneficialStrong communication skills with the ability to work across technology, data, infrastructure, security, and business teamsSkills SetAI engineeringMachine learning engineeringMLOpsGenerative AIProduction AI deploymentPythonAPI developmentMicroservicesTensorFlowPyTorchscikit‑learnMLflowKubeflowAirflowCI/CD for machine learningModel lifecycle managementModel governanceRetrieval‑augmented generationEmbeddingsVector databasesFeature storesData lakesQuantizationModel compressionDistillationTerraformHelmKubernetesSecure AI platformsWhy Join UsWork on enterprise AI platforms within a leading UAE‑based group with strong investment in digital transformation and intelligent automationBuild and deploy scalable AI systems that support data‑driven decisions, operational efficiency, and business innovation across multiple sectorsGain hands‑on exposure to generative AI, MLOps, RAG, model governance, cloud infrastructure, and production engineering at enterprise scaleCollaborate with technology, data, infrastructure, security, and strategy teams on reusable AI solutions with real business impactGrow in a future‑focused environment where AI engineering, responsible governance, and scalable platform development are becoming core business capabilitiesAbout the CompanyMajid Al Futtaim is a leading UAE‑headquartered business group with operations across retail, communities,