AI Architect (M/F)

About the role

Africa Global Logistics Rwanda Limited, a transport and logistics company based in Kigali, Rwanda, is hiring an AI Architect (M/F) for its AI Factory within the Digital & Innovation Department. You will define, design and govern the overall AI architecture so that all AI solutions are scalable, secure, interoperable and aligned with AGL's information system and industrial standards. The position is permanent and full time.

Key responsibilities

• Define and own the AI Factory's target architecture, including reference architectures, design principles and technical standards, and act as technical leader submitting architecture documents to the Architecture and Security Board.
• Design end-to-end AI solution architectures covering data ingestion, model training, inference, serving layers and monitoring, and drive build vs. buy decisions on foundation models, platforms and tooling.
• Maintain the AI technology stack (LLMs, orchestration frameworks, vector databases, MLOps platforms, cloud services) and keep a technology radar.
• Standardize RAG architectures and agent-based systems, including prompt strategies, guardrails and multi-agent orchestration patterns.
• Integrate AI solutions with core systems such as ERP and TMS, defining API standards, event-driven architectures and data contracts.
• Enforce AI-specific security standards, model access control, data protection and protection against prompt injection and adversarial inputs.

Required profile

• Master's degree or equivalent in Computer Science, Software Engineering, Data Science, AI or a related field.
• 3 to 5 years of experience in software architecture, data engineering or AI/ML engineering, including at least 3 years in an architecture or technical leadership role.
• Proven track record designing and deploying large-scale, production-grade AI systems in complex enterprise environments.
• Experience with enterprise information systems (ERP, data platforms, APIs, event-driven architectures).
• Exposure to governance, security and regulatory constraints is strongly valued; multinational or multi-site experience is an advantage.

Required skills

• Cloud architecture, preferably Microsoft Azure (Azure AI Foundry, Azure OpenAI, Azure ML), including AI workloads in enterprise or hybrid environments.
• LLM ecosystems and GenAI architectures: RAG pipelines, agentic workflows, multi-model orchestration and prompt strategies.
• AI orchestration frameworks and tooling integrated into production systems.
• System integration patterns: API design, microservices, event-driven architectures.
• MLOps and LLMOps concepts, including CI/CD pipelines and model lifecycle management.