Applied AI Engineer

Join Zapier as an Applied AI Engineer, where you'll play a crucial role in building and evolving the shared infrastructure that powers AI and ML development across the company. You'll work at the intersection of platform engineering, applied AI, and developer experience, making it easier for teams to build with LLMs and ML systems in a scalable, secure, and production-ready way. Your work will focus heavily on LLM Ops and ML Ops, improving how models are accessed, monitored, evaluated, deployed, governed, and operated in production.

• Contribuer à l'infrastructure partagée qui alimente le développement de l'IA et de l'apprentissage automatique chez Zapier.
• Développer et maintenir des services essentiels tels que notre serveur proxy LLM, les API de la plateforme et les outils réutilisables.
• Collaborer étroitement avec les ingénieurs des équipes produit, infrastructure et données pour garantir que nos composants d'IA sont réutilisables, bien documentés et faciles à adopter.
• If you’re passionate about large language models, machine learning systems, developer platforms, and building tools that help other engineers move faster, we’d love to meet you!
• Even though our job description may seem like we're looking for a specific candidate, the role inevitably ends up tailored to the person who applies and joins. Regardless of how well you feel you fit our description, we encourage you to apply if you meet these criteria:
• You embody our values. At Zapier, our values are at the heart of how we work together and how we think about our customers. In our remote setting, they help develop trust and ensure we work and collaborate to democratize automation
• You enjoy working collaboratively and learning from others. You’re excited to partner with more senior engineers and cross-functional teams to build reusable platform capabilities that make AI and ML development easier across the company
• You are thoughtful about engineering trade-offs and are developing a strong understanding of how to balance reliability, latency, cost, quality, and maintainability in production systems
• You have experience contributing to backend systems, developer tooling, internal platforms, or infrastructure that supports other engineers. You enjoy simplifying complex workflows and improving how teams build and ship software
• You have at least 1 year of experience in LLM Ops, ML Ops, or adjacent platform/infrastructure work. You’re interested in the practical challenges of operating these systems, including reliability, performance, safety, and cost
• You have 4+ years of experience in software engineering, including experience building and operating production AI/ML systems. You bring solid engineering fundamentals, good communication skills, and a desire to build reliable systems that others can depend on
• You have experience of working through the full lifecycle of building, testing, deploying, and scaling ML/ LLM architectures