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Applied AI Engineer, Prototyping

Mistral - Singapore, Singapore - In-office

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Mistral is a full-stack AI company providing frontier models, developer tools, applications, and compute infrastructure. They partner with enterprises across finance, manufacturing, defense, healthcare, and the public sector to co-create customized AI systems. As an Applied AI Engineer on the Proto team, you will lead the design and delivery of production-grade AI systems in rapid development cycles. The Proto team operates at the intersection of product and customer, translating advanced technology into real-world solutions that drive measurable business value. You will own end-to-end full-stack AI projects from scoping through deployment. This includes partnering with customers to clarify needs and architect robust systems, shipping ready-to-use applications for both external clients and internal teams, and leading technical architecture decisions to ensure scalability and reliability. You'll diagnose and solve complex technical problems across diverse industries and use cases, contribute to internal tools and product improvements, and evaluate new technology capabilities for integration into existing systems. Key responsibilities include translating complex business requirements into engineered solutions, guiding technical decisions in collaboration with internal teams and customers, pressure-testing what's possible to shape product direction, and unlocking new business opportunities through continuous product improvement. You bring at least 2 years of experience building and deploying production AI products or systems. You have strong Python skills with experience in scalable backend frameworks like FastAPI, and familiarity with modern GenAI stacks including RAG, agents, evaluation, and orchestration. You're comfortable with frontend development using React or Vue, and you excel at translating business needs into technical plans. You communicate complex technical ideas clearly to diverse stakeholders and have a track record of effective cross-team collaboration.

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