AI Engineer – LLMs, Generative AI, MLOps & Applied AI

Location: Dubai, UAE – OnsiteExperience Required: 4–8+ Years in Artificial Intelligence, Machine Learning, or AI EngineeringIndustry: Technology / Consumer Applications / On-Demand Services / Digital MarketplacesKey ResponsibilitiesDesign, develop, deploy, and maintain Artificial Intelligence (AI), Machine Learning (ML), Large Language Models (LLMs), and Generative AI solutions for a fast-growing consumer technology and on-demand services platform.Build and integrate LLM-powered applications, intelligent automation, AI assistants, conversational AI, and recommendation systems to enhance customer experience, operational efficiency, and platform capabilities.Develop and implement Applied AI solutions that address real-world business challenges across consumer applications, digital marketplaces, service delivery, and customer engagement.Design, develop, and optimize Machine Learning models for predictive analytics, customer behavior analysis, personalization, intelligent recommendations, and operational decision-making.Build and maintain scalable MLOps pipelines for model training, evaluation, deployment, monitoring, versioning, and continuous improvement.Develop and deploy Retrieval-Augmented Generation (RAG) pipelines, semantic search capabilities, vector databases, and knowledge retrieval systems for LLM-powered applications.Integrate LLM APIs and AI services, including OpenAI, Anthropic Claude, Google Gemini, or equivalent models, into production applications and backend services.Implement Prompt Engineering, LLM Fine-Tuning, Model Evaluation, and AI Optimization techniques to improve model accuracy, reliability, performance, and cost efficiency.Develop AI-powered features for mobile applications, web platforms, digital marketplaces, and on-demand consumer services.Collaborate with Backend Engineers, Mobile Engineers, Product Managers, and Founders to identify AI opportunities, define technical requirements, and deliver production-ready AI capabilities.Build and maintain Python-based AI services, REST APIs, microservices, and backend integrations to support AI-powered product features.Design and implement AI Agent workflows, intelligent automation, tool-calling systems, and multi-step AI orchestration where appropriate.Utilize AI development frameworks such as LangChain, LangGraph, LlamaIndex, Hugging Face Transformers, or similar technologies to accelerate AI application development.Work with Vector Databases, including Pinecone, Weaviate, FAISS, ChromaDB, or equivalent solutions, for semantic search and retrieval applications.Implement scalable AI infrastructure using AWS, Microsoft Azure, Google Cloud Platform (GCP), or similar cloud environments.Develop and maintain CI/CD pipelines, Docker containers, Kubernetes deployments, and automated ML workflows to support reliable AI model deployment.Monitor AI model performance, latency, accuracy, hallucinations, data quality, inference costs, and production reliability.Conduct AI model testing, performance benchmarking, experimentation, and continuous optimization to ensure high-quality production AI systems.Support AI-driven personalization, intelligent search, service matching, demand forecasting, customer support automation, and operational optimization where relevant to the platform.Ensure AI solutions follow appropriate Data Privacy, Security, Responsible AI, and Model Governance practices.Troubleshoot production AI systems, resolve model performance issues, and optimize inference pipelines for scalability and efficiency.Stay updated with emerging developments in Generative AI, LLMs, Agentic AI, Applied Machine Learning, and MLOps, identifying opportunities to introduce practical AI capabilities into the product.Contribute to AI architecture decisions, technical documentation, engineering best practices, and the long-term AI development roadmap.Experience & Professional Qualifications4–8+ years of relevant experience in Artificial Intelligence, Machine Learning Engineering, Applied AI, Data Science, or AI Software Development, with demonstrated experience delivering production AI solutions.Strong hands-on experience with Large Language Models (LLMs), Generative AI, MLOps, and Applied AI.Proven ability to design, develop, integrate, and deploy AI/ML models and LLM-powered applications into real-world production environments.Advanced programming skills in Python, with practical experience developing AI applications, machine learning pipelines, backend services, and API integrations.Strong understanding of Machine Learning, Deep Learning, Natural Language Processing (NLP), Generative AI, and Transformer-based architectures.Hands-on experience with LLM frameworks and APIs, including OpenAI, Anthropic Claude, Google Gemini, Hugging Face, or similar technologies.Practical experience with Prompt Engineering, Retrieval-Augmented Generation (RAG), Embeddings, Vector Search, and LLM Evaluation.Experience developing applications using LangChain, LangGraph, LlamaIndex, or equivalent LLM orchestration frameworks.Strong knowledge of MLOps principles and practices, including model deployment, experiment tracking, model versioning, monitoring, retraining, and lifecycle management.Experience with MLflow, Kubeflow, AWS SageMaker, Azure Machine Learning, Vertex AI, or equivalent MLOps platforms.Proficiency with machine learning frameworks such as PyTorch, TensorFlow, Scikit-learn, or similar technologies.Experience designing and deploying scalable, production-grade AI systems with appropriate performance, reliability, and cost optimization.Strong experience building and integrating REST APIs, FastAPI, Flask, or equivalent Python-based backend frameworks.Familiarity with Docker, Kubernetes, CI/CD pipelines, Git, and cloud-based deployment environments.Experience working with AWS, Microsoft Azure, or Google Cloud Platform, particularly for AI/ML infrastructure and application deployment.Knowledge of SQL, NoSQL databases, data pipelines, data processing, and database integration for AI-powered applications.Familiarity with Vector Databases, including Pinecone, Weaviate, FAISS, ChromaDB, or equivalent solutions.Experience with AI Agents, Agentic AI, Multi-Agent Systems, and Intelligent Workflow Automation is highly advantageous.Understanding of LLM Fine-Tuning, LoRA, Quantization, Model Optimization, and Inference Performance is advantageous.Experience developing recommendation engines, personalization models, predictive analytics, intelligent search, or customer behavior models is highly desirable.Experience working with consumer-facing mobile applications, digital marketplaces, on-demand service platforms, or super apps is strongly preferred.Candidates with previous experience at Careem, CAFU, Talabat, Deliveroo, Noon, Uber, or similar consumer technology, marketplace, mobility, or on-demand platforms are highly desirable.Experience building AI capabilities for service marketplaces, ride-hailing, delivery platforms, e-commerce, logistics, or consumer technology applications is advantageous.Demonstrated ability to translate business requirements and product challenges into practical, scalable, and commercially valuable AI solutions.Experience collaborating closely with Product Managers, Software Engineers, Backend Developers, Mobile Engineers, and cross-functional product teams.Strong understanding of AI Model Evaluation, Hallucination Detection, Model Monitoring, Responsible AI, Data Privacy, and AI Security.Ability to work in a startup, scale-up, or fast-paced product engineering environment, taking ownership of AI solutions from initial concept through production deployment.Strong analytical thinking, problem-solving, technical troubleshooting, communication, and stakeholder collaboration skills.Ability to work independently, manage competing priorities, and deliver AI features in an agile, product-driven engineering environment.Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, or a related technical discipline is preferred.Relevant certifications in AWS Machine Learning, Azure AI Engineer, Google Professional Machine Learning Engineer, or equivalent AI/ML technologies are advantageous.