Senior Data & AI Architect for Enterprise & Gov

Datamatics Technologies; Pakistan; On-site; PKR 33,306,000 - 49,958,000; Full time

Job summary

Datamatics Technologies is seeking a Data & AI Architect to lead enterprise data architectures in a KSA onsite role. You will design data models, warehousing, MDM and build AI/ML systems in production, while managing cloud data platforms and modern data stacks.

You will oversee AI/ML lifecycle including model selection, MLOps, deployment, and monitoring, and architect GenAI/LLM solutions with RAG pipelines and vector databases. Strong collaboration with engineering and executives is required.

Qualifications

• 8+ years in data architecture with AI/ML in production.
• Strong SQL skills and Python or similar language.
• Hands-on experience with Azure/AWS/GCP and modern data stacks.
• Experience designing data governance and enterprise data models.
• Ability to translate business requirements into technical architecture.

Responsibilities

• Design enterprise data architectures including data modeling, warehousing, and MDM.
• Design AI/ML systems in production environments.
• Develop and manage cloud data platforms and data pipelines.
• Oversee AI/ML lifecycle: model selection, MLOps, deployment, monitoring.
• Architect LLM/GenAI solutions including RAG, vector DBs, prompts.
• Translate business requirements into technical architecture for engineering teams.
• Design APIs and system integrations across platforms.
• Ensure alignment with data governance and compliance frameworks.
• Support smart-city, government, and enterprise initiatives with multiple stakeholders.

Skills

Data Engineering

Data Architectures

AI Engineering

SQL

Python

Cloud Platforms

Tools

Kafka

TOGAF

Job description

Datamatics Technologies is seeking a Data & AI Architect to lead enterprise data architectures in a KSA onsite role. You will design data models, warehousing, MDM and build AI/ML systems in production, while managing cloud data platforms and modern data stacks.

You will oversee AI/ML lifecycle including model selection, MLOps, deployment, and monitoring, and architect GenAI/LLM solutions with RAG pipelines and vector databases. Strong collaboration with engineering and executives is required.