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Mistral is seeking Backend Engineers to join its NYC team and contribute to core systems powering its AI platform products: AI Studio, Le Chat, and Mistral Code. The company provides full-stack AI solutions—from frontier models to developer tools and applications—partnering with enterprises across finance, manufacturing, defense, healthcare, and the public sector to build customized AI systems.
In this role, you will design, develop, and maintain scalable, robust backend features and APIs using modern frameworks. You'll ensure high performance and reliability across distributed systems, contributing to infrastructure powering inference, billing, AI tooling, observability, and developer experience. Key responsibilities include designing efficient, secure, and scalable architectures that support fast-growing products; collaborating with infrastructure teams on deployment, monitoring, and performance optimization; writing clean, maintainable, well-documented code; and participating in code reviews to establish technical standards.
You'll work cross-functionally with product managers, platform engineers, and AI/ML teams to design and deliver scalable model-as-a-service solutions for developers and enterprise users. You'll tackle complex engineering challenges—from distributed systems to AI product integration—and stay current with emerging technologies like AI/LLM integration, observability tools, and backend frameworks.
Required qualifications include a degree in Computer Science, Software Engineering, or equivalent practical experience; proficiency in Python or another backend language (Golang, Kotlin, C#); strong understanding of backend fundamentals (APIs, databases, caching, messaging systems, distributed architectures); strong problem-solving abilities and attention to detail; ownership mindset for shipping end-to-end features; excellent communication skills; and a team-oriented, low-ego, curious mindset.
Ideal candidates have full-stack exposure, experience with API and developer ecosystems, deployment to diverse environments (cloud, on-premises), infrastructure management (Docker, CI/CD, Kubernetes, Helm, Terraform), AI/ML engineering background, observability and monitoring tools (Prometheus, Grafana, Datadog), and a UX/product-centric mindset.
