Mistral AI
Software Engineer, Backend
About this role
Mistral seeks a Backend Engineer in NYC to build scalable, high-performance APIs and core systems powering their AI platform (AI Studio, Le Chat, Mistral Code). You'll collaborate across teams to design robust distributed systems serving millions of users while integrating AI/LLM capabilities into production.
What you'll do
- Design and develop scalable backend features and APIs using modern frameworks
- Build systems supporting inference, billing, AI tooling, observability, and developer experience
- Architect efficient, secure, and scalable solutions collaborating with infrastructure teams
- Write clean, maintainable code and participate in code reviews and technical standards
- Partner with product, platform, and AI/ML teams to deliver model-as-a-service solutions
- Tackle distributed systems challenges and integrate emerging technologies like LLMs into production
What they're looking for
- Python or backend languages (Go, Kotlin, C#)
- APIs, databases, caching, messaging systems, and distributed architectures
- Problem-solving and attention to detail
- Infrastructure/DevOps (Docker, CI/CD, Kubernetes, Terraform)
- System design and architecture
- API and developer ecosystem experience
- Observability and monitoring tools (Prometheus, Grafana, Datadog)
- AI/ML engineering or LLM integration knowledge
Benefits
- Work on frontier AI products serving enterprise and developer users
- Collaborate with distributed, passionate team across Europe, North America, Asia, and Middle East
- Ownership of end-to-end features with autonomy
- Exposure to cutting-edge AI/LLM technologies and real-world scaling challenges
- Low-ego, collaborative culture emphasizing innovation
- Career growth from mid-level to senior/staff engineer roles
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Mistral AI
Mistral AI builds large-scale machine learning systems and open-weight AI models, supported by infrastructure powering petabyte-scale HPC clusters and enterprise AI platforms. The company is hiring Systems Engineers, Research Engineers, Site Reliability Engineers, and Applied AI Engineers to scale training infrastructure, optimize data systems, ensure platform reliability, and drive customer adoption across industries.
- Website
- mistral.ai
Likely interview questions
- Walk us through designing a scalable API to serve inference requests at millions of scale—what trade-offs would you consider?
- Describe your experience integrating external services or models into production; how did you handle failure scenarios?