AI Engineer (French Speaker)

Rejoignez Distyl, une entreprise innovante spécialisée dans l'IA. En tant qu'Ingénieur IA, vous serez responsable de la conception, de l'implémentation et de l'exploitation de systèmes IA de bout en bout, en étroite collaboration avec les clients et les experts en la matière. Vous devez être fluent en français et avoir au moins 5 ans d'expérience en ingénierie logicielle.

• Concevoir, mettre en œuvre, déployer et itérer sur des systèmes d'IA de bout en bout en étroite collaboration avec les clients.
• Construire et exploiter des systèmes d'IA déployés dans des environnements clients, en prenant la responsabilité du comportement, de la fiabilité et de l'utilité du système en production.
• Traduire les besoins opérationnels en comportements concrets du système, construire le logiciel et les flux de travail d'IA nécessaires pour soutenir ce comportement.

• AI-native working style. You use AI tools daily to write and debug code, explore designs, analyze data, and automate repetitive work. You are curious about new model capabilities and techniques, and actively incorporate them into how you build and iterate on systems
• Fluent in French (Written and Spoken) with the ability to lead technical discussions and collaborate directly with French-speaking clients
• Comfort in customer environments. You are able to work directly with customer teams, ask good questions, and adapt quickly to new domains. You communicate clearly about system behavior, limitations, and tradeoffs, and can operate effectively in high-trust, high-visibility situations
• Willingness to travel. Travel is typically 10–30%, depending on the project, customer needs, and your role on the engagement
• 5+ years of software engineering experience
• Strong engineering fundamentals. You write clean, maintainable Python and are comfortable building production software systems. You understand core engineering concepts like versioning, debugging, testing, performance, code review, and production readiness
• Pragmatic delivery mindset. You can navigate ambiguity, make progress with incomplete information, and balance speed with robustness when building systems that need to work for production users
• Experience building AI systems. You have built applications powered by LLMs or other AI models and are comfortable composing multiple components — prompts, agents, tools, retrieval, evaluators, workflows, and integrations — into end-to-end systems. You reason about system behavior holistically rather than treating models as black boxes
• Ownership mentality for AI systems. You take responsibility for whether the systems you build deliver their intended value in production. You are comfortable making technical decisions, learning from system behavior, and owning the results of your work