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Mistral AI

Open-weight LLMs and enterprise AI deployment

Software Engineer - Golang, Serverless Containers

Backend EngineeringConfirmed live in the last 24 hours
Full-timeParis, FranceNo salary listedRemote

About the Job

Requirements

  • You have shipped production systems in Go.
  • You have built container or workload platforms, including orchestration, scheduling, isolation, or request routing, rather than only deploying onto another company's serverless platform.
  • You have deep Linux knowledge, including namespaces, control groups (cgroups), image layers, and page cache, and are comfortable working below the application layer.
  • You have multi-tenancy instincts covering density, isolation, and fairness when hundreds of customers share one fleet.
  • You have significant experience building complex backend or infrastructure systems.
  • You have partnered with product, design, and business teams to ship software that reached real users.

Responsibilities

  • Build the container platform end to end, including image delivery, placement, request routing, scale-up, and scale-to-zero across CPU and GPU.
  • Solve cold starts through techniques such as snapshotting, prewarming, and image-layer caching so scale-from-zero feels instant.
  • Build for AI workloads, including GPU-backed containers, streaming responses, long-lived connections, and MCP servers that cost almost nothing while idle.
  • Write Go and own the architecture and the hardest implementation decisions.
  • Partner with Product Managers to turn platform decisions into a product developers want to deploy on.

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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