# AI Architect — Net2Source (N2S)

Canonical: https://jobxdubai.com/jobs/li-4448830257-ai-architect
Location: Dubai, UAE
Type: contract · Level: senior
Monthly salary: AED 20,000 to 20,000 per month (employer-stated) (UAE salaries are tax-free)
Posted: 2026-08-04
Apply: https://www.linkedin.com/jobs/view/ai-architect-at-net2source-n2s-4448830257?_l=en

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## Description

🚀 We're Hiring: AI Architect (12+ Years Experience) – Dubai, UAE

We're looking for an experienced AI Architect to join a leading enterprise project in Dubai, UAE.

📍 Location: Dubai, UAE

📄 Contract: 1 Year (Extendable)

💰 Salary: Up to AED 20,000/month

📌 Experience: 12+ Years

Key Responsibilities:

✅ Define end-to-end AI architecture for GenAI, Agentic AI, and ML platforms

✅ Design scalable LLM-based and multi-agent AI systems

✅ Establish AI platform standards, governance, and best practices

✅ Lead architecture discussions with engineering and business stakeholders

✅ Ensure security, compliance, scalability, and performance of AI solutions

✅ Evaluate AI tools, frameworks, and cloud platforms

✅ Provide technical leadership and mentor engineering teams

Required Skills:

🔹 12+ years of IT experience with strong AI/ML architecture expertise

🔹 Hands-on experience with LLMs, RAG, Agentic AI, and Multi-Agent Systems

🔹 Experience with LangChain, LangGraph, and AI orchestration frameworks

🔹 Strong knowledge of AWS, Azure, and/or GCP AI ecosystems

🔹 Enterprise architecture, integration patterns, and cloud-native solution design

🔹 Understanding of data pipelines, MLOps, and the ML lifecycle

🔹 Experience delivering large-scale enterprise AI transformation initiatives

If you're interested or know someone who would be a great fit, please send your updated resume or tag them in the comments.

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## Requirements

12+ years of IT experience with strong AI/ML architecture expertise. Hands-on experience with LLMs, RAG, Agentic AI, and Multi-Agent Systems. Experience with LangChain, LangGraph, and AI orchestration frameworks. Strong knowledge of AWS, Azure, and/or GCP AI ecosystems. Enterprise architecture, integration patterns, and cloud-native solution design. Understanding of data pipelines, MLOps, and the ML lifecycle. Experience delivering large-scale enterprise AI transformation initiatives.

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