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Mistral is a full-stack AI company providing frontier models, developer tools, applications, and compute infrastructure. They partner with enterprises across finance, manufacturing, defense, healthcare, and the public sector to co-create customized AI systems.
As an Applied AI Engineer, you will be the technical lead for AI adoption across Mistral's internal departments. Your mission is to make Mistral AI-native from the inside by designing and delivering production-grade AI systems that solve real business problems at scale.
You will work at the intersection of product, engineering, and business. Your responsibilities include:
- Conducting discovery with department heads and key users to map workflows and translate ambiguous business requirements into a prioritized use-case backlog with clear expected value.
- Delivering end-to-end solutions: designing and shipping production-grade full-stack applications (Python/FastAPI, React) and AI systems from scoping through deployment and adoption.
- Encoding business rules, KPIs, and ROI metrics as durable data lake assets and application logic to ensure departments run on trustworthy, observable data.
- Dogfooding the latest Mistral products as a first internal user and providing credible product feedback that shapes the roadmap.
- Owning architecture for your domain: keeping it scalable, secure, and observable with high standards for clean code.
- Identifying patterns across departments and lifting one-off solutions into reusable building blocks.
You will act as both a technical leader and individual contributor, guiding technical choices, building solutions end-to-end, driving adoption, and continuously improving systems. Your goal is to build internal stakeholder trust and deliver high-ROI solutions, not quick POCs.
REQUIREMENTS:
- Minimum 3 years building and deploying production AI software
- Strong full-stack engineering skills: Python/TypeScript, scalable backends (FastAPI/Node), and sufficient frontend (React/Vue) to ship usable applications independently
- Hands-on experience with modern GenAI use cases: RAG, agents, workflows, orchestration, and evaluation
- Strong command of AI-native development tools paired with genuine care for clean code and architecture
- Strong ownership mindset and bias for delivery; experience as a high-velocity engineer
- Fluency with AI-native tools (Slack, Linear, etc.)
- Passion for solving customer problems (in this case, Mistral's internal teams)
- Excellent communication skills in fluent English; ability to explain technical concepts to diverse audiences (lawyers, marketers, staff engineers)
NICE TO HAVE:
- Exposure to Legal, Public Affairs, Marketing, or Compute/Infrastructure domains, or proven ability to get fluent in unfamiliar domains quickly
- Data engineering or analytics experience (warehouse modeling, dbt, dashboards)
- Open-source contributions, especially around LLMs
- Builder's instinct for internal tooling and platform reuse
