AI Architect

Job Description

Job Role: AI Architect

Job Location: Dubai

Job Role

We are seeking a highly experienced and visionary AI Architect with 15+ years of expertise in designing and implementing AI/ML solutions across diverse industries. The ideal candidate will have deep technical knowledge, strong business acumen, and the ability to lead cross-functional teams in driving AI innovation and enterprise-wide adoption. You will be responsible for defining AI strategy, building scalable architectures, and ensuring the alignment of AI initiatives with business objectives.

Roles & Responsibilities

• Define the enterprise AI strategy and roadmap, aligning with organizational goals.
• Design and architect end-to-end AI/ML systems, including data pipelines, model development, deployment, monitoring, and governance.
• Lead the evaluation and selection of AI tools, frameworks, and cloud platforms (e.g., Azure AI, AWS SageMaker, GCP Vertex AI).
• Collaborate with data scientists, engineers, business analysts, and product teams to deliver AI-driven solutions.
• Guide AI model lifecycle management (MLOps), ensuring performance, scalability, and ethical compliance.
• Architect real-time and batch data processing pipelines for AI workloads using technologies like Spark, Kafka, Airflow, etc.
• Establish best practices for AI ethics, fairness, explainability, and regulatory compliance.
• Act as a thought leader in AI, presenting to C-level stakeholders and mentoring technical teams.
• Lead PoC development, feasibility studies, and AI solution evaluations.
• Partner with cybersecurity teams to ensure secure AI model operations and data privacy.
  
  

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related fields.
• 15+ years of experience in IT, with 8+ years in AI/ML development and 5+ years in AI architecture or leadership roles.
• Deep understanding of machine learning, deep learning, NLP, computer vision, and generative AI technologies.
• Proficiency with tools such as Python, TensorFlow, PyTorch, scikit-learn, MLflow, etc.
• Strong cloud expertise: Azure AI, AWS AI/ML, GCP AI, or hybrid cloud deployments.
• Solid grasp of microservices, API design, DevOps/MLOps practices, and container orchestration (e.g., Docker, Kubernetes).
• Experience in deploying models at scale in production environments.
• Knowledge of AI/ML compliance standards (e.g., GDPR, HIPAA, Responsible AI principles).
  
  

• Experience with LLMs, RAG architectures, and prompt engineering.
• Familiarity with AutoML, Reinforcement Learning, and AIOps.
• Published research or patents in AI/ML is a strong plus.
• Certification in cloud AI/ML platforms (Azure AI Engineer, AWS ML Specialty, etc.)