AI Architect

Job Summary

Systems Arabia is seeking an experienced AI Architect with 10+ years of IT experience to design, architect, and govern enterprise-scale AI solutions. The role involves leading AI strategy, cloud-native platform design, and Generative AI implementation while collaborating with business and technical teams.

Responsibilities

• Define enterprise AI strategy, architecture roadmap, and governance framework aligned with business objectives.
• Design scalable, secure, cloud-native AI platforms for enterprise-wide AI adoption.
• Architect Generative AI solutions using LLMs, RAG frameworks, AI Copilots, Chatbots, and Intelligent Knowledge Systems.
• Design and implement Agentic AI and Multi-Agent Systems to automate complex business processes.
• Build end-to-end AI/ML platforms including model development, deployment, monitoring, and optimization.
• Lead implementation of NLP, Computer Vision, Recommendation Engines, Forecasting, and Predictive Analytics solutions.
• Architect AI-ready data platforms, data lakes, vector databases, and enterprise knowledge repositories.
• Establish MLOps/LLMOps practices, CI/CD pipelines, observability, and governance standards.

Requirements

• 10+ years of experience in AI, Machine Learning, Data Engineering, Solution Architecture, or related domains.
• Strong expertise in AI/ML, Deep Learning, NLP, Computer Vision, Predictive Analytics, and Generative AI solutions.
• Hands-on experience with LLMs, RAG, Prompt Engineering, AI Agents, Agentic AI, Multi-Agent Systems, and AI Copilot development.
• Proven experience with OpenAI, Azure OpenAI, Claude, Gemini, Llama, and other leading AI platforms.
• Proficiency in LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, TensorFlow, PyTorch, and Hugging Face.
• Strong programming skills in Python and SQL with experience building APIs, microservices, and enterprise applications.
• Experience with Vector Databases, Knowledge Retrieval Systems, and Enterprise Search platforms.
• Expertise in building AI-ready data platforms using Databricks, Spark, Kafka, and Airflow.
• Strong experience with Microsoft Azure, AWS, and/or Google Cloud AI and Machine Learning services.
• Solid understanding of MLOps, LLMOps, DevOps, CI/CD, Docker, Kubernetes, MLflow, and AI observability practices.

We refresh listings regularly, but some roles close early on the source platform.