R-ainbow Marketplace
Artificial Intelligence Engineer
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Company Description
R-ainbow Marketplace is a mission-driven digital platform focused on empowering the 525 million smallholder farmers who produce most of the world’s food yet often sell at a loss. The company is transforming the food supply chain and food tech industry by reducing waste caused by outdated distribution systems and market inefficiencies, which can result in 30–40% of harvests being lost.
R-ainbow operates as an online marketplace that connects small producers with buyers in real time, using data on product availability, location, and stock levels to enable efficient, cost-effective transactions. The app makes buying and selling produce more accessible, convenient, and sustainable, and can be used anywhere. R-ainbow has been recognized as a 2023 EU Tech Chamber SDG Award finalist for “Zero Hunger” and was honored in 2024 at Westminster Abbey in the historical book “The Commonwealth at 75.”
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Role Description
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We are looking for an experienced backend developer who can build scalable backend systems and work closely with AI models. The role requires someone who understands both traditional backend development and applied AI, including using company data to train, fine-tune, evaluate, and improve models.
Key Responsibilities
- Design and build secure, scalable backend services and APIs
- Improve API speed, reliability, database performance, and resource usage
- Work with third-party, self-hosted, and in-house AI models
- Prepare, structure, and manage internal data for AI training
- Build model training, fine-tuning, evaluation, and inference pipelines
- Use techniques such as RAG, embeddings, semantic search, and vector databases
- Connect AI models with live business data and backend services
- Build background jobs, queues, caching, event tracking, and monitoring
- Measure model accuracy, response time, cost, and output quality
- Prevent AI models from returning incorrect or unverified business data
- Help decide whether to use external models, open-source models, or internally trained models
- Create a backend foundation that can support growing data, traffic, and AI use cases
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