Principal AI / ML Architect — GCP Vertex AI

 We are looking for a highly experienced Principal AI / ML Architect to design and deliver enterprise-grade AI and machine learning solutions on Google Cloud Platform.

The client is a public sector organization in Saudi Arabia developing several internal AI initiatives, including RAG-based assistants, semantic search, document intelligence, forecasting, and predictive analytics.

Responsibilities

• Design end-to-end AI and ML solution architectures on GCP.
• Lead the development and deployment of production AI systems.
• Build solutions using Python, Vertex AI, BigQuery, Gemini, and LangChain or similar frameworks.
• Architect RAG pipelines, semantic search, document retrieval, and vector search systems.
• Develop forecasting and predictive modelling solutions.
• Design scalable APIs, data pipelines, and MLOps workflows.
• Define technical standards for security, reliability, performance, and cost optimisation.
• Provide technical leadership and architecture guidance to engineering teams.
• Communicate with enterprise and public sector stakeholders.
• Prepare architecture diagrams, technical documentation, and implementation plans.

Requirements

• 15+ years of professional IT experience.
• Strong recent hands-on experience with AI, ML, or data platforms.
• Deep expertise in Google Cloud Platform.
• Production experience with Vertex AI and BigQuery.
• Strong Python skills.
• Experience building production RAG and semantic search solutions.
• Strong knowledge of LLMs, embeddings, vector databases, and document processing.
• Experience with forecasting, predictive modelling, or classical ML.
• Strong understanding of cloud architecture, APIs, data pipelines, and distributed systems.
• Experience leading architecture and technical delivery on large enterprise projects.
• English at Upper-Intermediate level or higher.

Nice to Have

• Experience with Saudi Arabian, government, or public sector clients.
• Experience with Gemini, Document AI, Vertex AI Search, or Agent Builder.
• Experience with GKE, Docker, Kubernetes, CI/CD, and MLOps.
• Google Cloud certifications.
• Experience with security, compliance, and regulated enterprise environments.

Project Details

• Full-time engagement.
• Long-term public sector project.
• Remote work.
• Start date: as soon as possible.
• Hourly or monthly rate is negotiable.