Technical Lead, Applied AI Engineer — Full-Stack

Mistral; Paris; Sur place; EUR 90 000 - 130 000; Plein temps

Résumé du poste

Mistral AI is seeking an Applied AI Engineer to lead production-grade AI systems from scoping to deployment. You will work across GTM, engineering, and applied AI, translating ambiguous business problems into working software and owning architecture end to end.

You will collaborate with customers and internal teams, driving from prototyping to deployment with high autonomy and velocity, while shaping product direction with real-world usage insights.

Qualifications

• 2+ years of hands-on experience shipping AI-powered products.
• Proven ability to build and deploy production systems end-to-end.
• Experience with LLMs, RAG, agentic systems and their deployment.
• Strong Python backend engineering with FastAPI and Pydantic.
• Frontend experience with React or Vue to build usable interfaces when needed.
• Broad expertise across system design, infrastructure (Kubernetes) and applied AI problem-solving.

Responsabilités

• Build and deliver full-stack AI solutions for global customers, leading end-to-end execution from scoping to deployment.
• Engage directly with customers to understand use cases and translate them into robust architectures.
• Collaborate across GTM, product, and engineering to ship solutions and contribute to internal tools and open-source initiatives.
• Solve complex applied AI problems across industries, providing hands-on technical guidance throughout engagements.

Connaissances

Hands-on AI engineer

Full-stack development

Python

Frontend development

Docker

Kubernetes

Terraform

FastAPI

Outils

Docker

Kubernetes

Terraform

Description du poste

Mistral AI is seeking an Applied AI Engineer to lead production-grade AI systems from scoping to deployment. You will work across GTM, engineering, and applied AI, translating ambiguous business problems into working software and owning architecture end to end.

You will collaborate with customers and internal teams, driving from prototyping to deployment with high autonomy and velocity, while shaping product direction with real-world usage insights.