AI Architect

About the role

Based at the AGL Expertise Center in Kigali, you will join the AI Factory within the Digital & Innovation Department as an AI Architect. You will be responsible for defining, designing and governing the overall AI architecture, ensuring solutions are scalable, secure, interoperable and aligned with enterprise standards.

Key responsibilities

• Define and own the AI Factory's target architecture, including reference architectures, design principles and technical standards.
• Design end‑to‑end AI solution architectures covering data ingestion, model training, inference, serving and monitoring.
• Standardize architecture patterns to ensure consistency, scalability and reuse across AI use cases.
• Lead technology evaluation and make‑or‑buy decisions for foundation models, platforms and tooling.
• Design and standardize Retrieval‑Augmented Generation (RAG) and agent‑based architectures, including prompt strategies and output validation.
• Design integration architectures linking AI solutions to core enterprise systems such as ERP, TMS and data platforms.
• Define and enforce AI‑specific security, compliance and model protection standards.

Required profile

• Master’s degree in Computer Science, AI, Data Science or a related field.
• 3–5 years of experience in software or AI/ML architecture, with at least 3 years in a technical leadership role.
• Proven track record of delivering large‑scale, production‑grade AI systems in complex enterprise environments.
• Strong background in cloud architecture, preferably Microsoft Azure, and integration with enterprise information systems.
• Experience with modern AI paradigms such as Large Language Models, RAG and agent‑based systems.

Required skills

• Design of large‑scale AI/ML pipelines and architectures.
• Microsoft Azure AI services (Azure AI Foundry, Azure OpenAI, Azure ML).
• Large Language Model ecosystems and GenAI patterns.
• RAG pipelines, vector stores and retrieval optimization.
• AI orchestration frameworks and MLOps/LLMOps tooling.
• API design, event‑driven and micro‑service integration with ERP/TMS.
• AI security, model protection and data privacy.
• Python programming, version control, testing and containerisation.