AI Engineer (LLM & Agents) – Kigali

About the role

Africa Global Logistics Rwanda Limited, a transport and logistics company based in Kigali, Rwanda, is hiring an AI Engineer (M/F) for its AI Factory within the Digital & Innovation Department. You will design, develop and industrialize production-grade AI solutions based on LLMs and agent architectures, contributing to high-value AI use cases across the group.

Key responsibilities

• Design and build end-to-end AI applications with LLMs, integrating Azure AI Foundry services, APIs and enterprise systems, with a focus on scalability, reliability and performance.
• Develop and optimize Retrieval-Augmented Generation (RAG) pipelines, including data ingestion, chunking, embeddings and vector search.
• Design autonomous and orchestrated AI agents that run complex workflows and support tasks such as document analysis, compliance and operational decision support.
• Fine-tune models and improve performance through prompt engineering, context optimization and model adaptation, weighing RAG, fine-tuning and model choice.
• Define evaluation and benchmarking frameworks for accuracy, latency and cost, and set up monitoring and feedback loops.
• Deploy, monitor and maintain AI solutions in production on Azure, with CI/CD pipelines, observability and performance tracking.
• Ensure compliance with AI governance, security and regulatory requirements, including guardrails, traceability and responsible AI practices.
• Work with AI Architects and business stakeholders to deliver reusable, high-impact solutions and improve AI Factory standards and tools.

Required profile

• Bachelor's or Master's degree in Computer Science, AI, Software Engineering, Data Science or a related field.
• At least 2 years of experience in software engineering, AI engineering or machine learning, with production-grade applications.
• Experience building and deploying LLM solutions, including RAG, prompt engineering and API-based model integration.
• Experience with cloud environments, preferably Microsoft Azure, and deployment of scalable AI solutions.
• Familiarity with MLOps practices (CI/CD, monitoring, model lifecycle management).

Required skills

• Strong Python programming for clean, scalable code (APIs, microservices, integrations).
• Hands-on experience with LLM ecosystems, prompt engineering and foundation models via APIs.
• RAG architectures: document processing, chunking, embeddings and vector search.
• AI orchestration frameworks and agent-based systems, including tool calling and Model Context Protocol (MCP) integrations.
• Azure services such as Azure AI Foundry, Azure OpenAI, Azure ML and Azure AI Search.
• MLOps, containerization (Docker), CI/CD, monitoring, logging and observability.