Software Engineer, New Grad

Mistral AI Mistral AI · AI Frontier · Paris, France · Engineering & Infra

Seeking early-career software engineers to join Mistral AI's software engineering teams. This role will focus on building and improving core systems for products like AI Studio and Applications, as well as supporting operations and user/developer interaction with the AI platform. Responsibilities include backend and frontend development, system architecture, infrastructure, code quality, and cross-functional collaboration. The role involves tackling real-world engineering problems and integrating new AI capabilities.

What you'd actually do

  1. Contribute to the design and implementation of backend features and APIs using modern frameworks.
  2. Design, develop, and maintain scalable and robust user-facing features (using TypeScript, React, Next.js) and ensure seamless integration between front-end and back-end systems using a modern stack.
  3. Learn how to design efficient, secure and scalable architectures under the guidance of more senior engineers.
  4. Write clean, readable and well-tested code.
  5. Work with product managers, front-end engineers, designers and data/AI engineers to deliver end-to-end features.

Skills

Required

  • Degree in Computer Science, Software Engineering or related field, or equivalent hands-on experience
  • Proficient with at least one programming language such as Python, JavaScript/TypeScript, C++, Golang
  • Solid understanding of core computer science and system architecture fundamentals
  • Built software projects through internships, personal projects, open-source contributions or university work
  • Enjoy solving problems, pay attention to detail and care about building reliable systems
  • Proactive, curious and willing to take ownership of small features end-to-end with guidance
  • Communicate clearly, ask good questions and enjoy working in a collaborative, low-ego environment

Nice to have

  • Infrastructure topics (Docker, CI/CD, Kubernetes, Helm, Terraform…)
  • AI/ML engineering or working with LLMs and related tooling
  • Observability and monitoring tools (Prometheus, Grafana, Datadog…)
  • UX and product-centric thinking

What the JD emphasized

  • core systems powering our products
  • AI platform at scale
  • AI capabilities