AI / ML Engineer I Dubai

About the role

Orient Insurance PJSC, part of Al-Futtaim, is looking for an experienced AI / ML Engineer in Dubai to design, build and operationalize AI and machine learning systems that deliver measurable business value. The role moves models from experimentation to robust, scalable production services, partnering with domain experts and product managers on classical ML, LLMs, RAG and emerging agentic AI workflows.

Key responsibilities

• Develop and integrate generative AI and LLM solutions, including prompt engineering, RAG, embeddings, vector search, fine-tuning and model evaluation.
• Design agentic AI workflows with orchestrators, sub-agents, tool/function calling and integrations via protocols such as the Model Context Protocol (MCP).
• Train and deploy machine learning and deep learning models for production use cases such as prediction, classification, NLP, recommendation and computer vision.
• Build end-to-end ML pipelines covering data ingestion, feature engineering, training, evaluation, deployment and monitoring.
• Operationalize models with MLOps practices: CI/CD for ML, versioning, automated retraining, A/B testing and drift monitoring.
• Collaborate with data engineers on data flows and feature stores, optimize inference for latency, throughput, scalability and cost, and implement observability and alerting.
• Embed responsible AI principles (fairness, explainability, security, privacy, compliance) and contribute to architecture, code reviews and documentation.

Required profile

• 3-7+ years of hands-on experience building and deploying AI/ML systems in production.
• Strong Python skills and software engineering fundamentals; proven experience with ML frameworks such as scikit-learn, PyTorch and/or TensorFlow.
• Experience deploying models as production services (REST/gRPC APIs, containerization, batch and real-time inference) and with SQL and data tools such as pandas or Spark.
• Experience with at least one major cloud platform (Azure, AWS or GCP) and its ML services, and familiarity with MLOps tooling.
• Preferred: fine-tuning foundation models, agentic frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel), RAG pipelines at scale, distributed training, streaming data, and domain experience in regulated industries such as financial services or insurance.
• Bachelor's or Master's degree in a relevant field; cloud/ML certifications are advantageous.

Required skills

• Python, SQL, scikit-learn, PyTorch, TensorFlow, Hugging Face Transformers
• LLMs and GenAI: OpenAI, Claude, Azure OpenAI, LangChain, LangGraph, LlamaIndex, MCP, FAISS, Pinecone, Weaviate, pgvector
• Cloud and ML platforms: Azure ML, AWS SageMaker, Google Vertex AI
• MLOps: MLflow, Docker, Kubernetes, CI/CD, Git, model registries