Position: Data & AI Architect
Location: KSA (Onsite)
Duration: 1 Year
Preferred Languages: English; Arabic is a plus
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Design enterprise data architectures including data modeling, data warehousing, and master data management.
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Design AI/ML systems in production environments.
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Develop and manage cloud data platforms (Azure/AWS/GCP) and modern data stack architectures including data lakes, lakehouse, ETL/ELT pipelines.
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Design and oversee AI/ML lifecycle activities including model selection, MLOps, deployment, and monitoring.
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Architect LLM/GenAI solutions including RAG pipelines, vector databases, prompt engineering, and model orchestration.
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Translate business requirements into technical architecture.
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Communicate effectively with engineering teams and executive stakeholders.
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Design APIs and system integrations for interconnected platforms and systems.
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Ensure alignment with data governance and compliance frameworks.
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Support smart-city, government, and enterprise platform initiatives involving multiple stakeholders and integrated systems.
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8+ years in data architecture, with 2–3+ years designing AI/ML systems in production.
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Strong hands-on experience with cloud data platforms (Azure/AWS/GCP) and modern data stack (data lakes, lakehouse, ETL/ELT pipelines).
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Proven experience designing enterprise data architectures (data modeling, data warehousing, master data management).
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Solid understanding of AI/ML lifecycle: model selection, MLOps, deployment, monitoring.
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Experience with LLM/GenAI architecture (RAG pipelines, vector databases, prompt engineering, model orchestration).
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Experience with data governance and compliance frameworks.
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Ability to translate business requirements into technical architecture and communicate with both engineering teams and executive stakeholders.
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Experience with API design and system integration.
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Data Engineering and Data Architectures – Moderate to Advanced.
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AI Engineering – Basic to Intermediate.
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Strong SQL.
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At least one programming language (Python most common).
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Direct experience with PDPL, NCA ECC, or NDMO frameworks, or similar.
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GDPR/HIPAA experience.
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AI Advanced Architectures.
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Familiarity with real-time/streaming data architectures (Kafka, event-driven systems).
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Experience with IoT data ingestion (parking sensors, city infrastructure, etc.).
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Enterprise architecture certifications (TOGAF, cloud architect certifications).
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Experience in government, smart city, or public-sector platforms.
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Vendor/multi-stakeholder environment experience (JV, consortium, or large enterprise with multiple business units).
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English (Preferred).
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Arabic language skills are a plus.
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