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