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Mistral AI

Open-weight LLMs and enterprise AI deployment

Applied AI Engineer - Prototyping

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listedIn-person

About the Job

Requirements

  • At least 2 years building and deploying production AI products or systems.
  • Strong experience with vibe coding tools, with high regard for clean code and high architecture standards.
  • Experience working with modern generative AI stacks, with expertise in retrieval-augmented generation, agents, evaluation, and orchestration.
  • Strong Python skills and experience with scalable backend frameworks such as FastAPI.
  • Familiarity with frontend development, ideally using frameworks such as React or Vue.
  • Ability to quickly understand business needs and translate them into technical plans.
  • Ability to explain complex technical ideas to diverse stakeholders.
  • Track record of collaborating effectively across different teams.

Responsibilities

  • Deliver end-to-end full-stack AI solutions from project scoping through deployment.
  • Partner with customers to clarify needs, define requirements, and architect robust systems.
  • Ship ready-to-use applications for clients and Mistral's internal teams.
  • Lead architecture and technical choices, ensuring solutions are scalable and reliable.
  • Diagnose and solve complex technical problems across industries and use cases.
  • Contribute to internal tools, product improvements, and open-source initiatives.
  • Evaluate and integrate new technology capabilities into existing systems.

About the Company

Mistral AI

Open-weight LLMs and enterprise AI deployment

Mistral AI builds open-weight large language models and the tools to run them, along with inference infrastructure and enterprise products that let organizations deploy AI with control over data residency, customization, and the underlying stack. Its platform provides open-model architectures and a deployment stack for inference, governance, and integration that can run on‑premises or in the cloud. This openness and modular stack differentiate it from single-vendor hyperscalers by prioritizing data locality and flexibility. The company aims to enable reliable, customizable AI deployment at scale for businesses and public-sector customers across many countries.

Company size
1,001-5,000
Company stage
Series D
Total funding
$7.2B
Headquarters
Paris, France
Founded
2023

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