Sr. Applied AI Engineer

Responsibilities

• Build and evolve shared AI Platform capabilities that serve as the foundation for teams building with machine learning and generative AI across Zapier.
• Improve LLM Ops and ML Ops capabilities, including observability, monitoring, evaluation, deployment workflows, and operational guardrails.
• Design and implement systems that help teams measure and improve the performance, reliability, safety, and cost efficiency of AI-powered experiences.
• Proactively identify tooling gaps and work across teams to standardize best practices for building, deploying, and monitoring AI-driven experiences.
• Collaborate closely with engineers across product, infra, and data teams to ensure AI components are reusable, well-documented, and easy to adopt company-wide.
• Evaluate emerging tools, models, and patterns in the AI ecosystem, and help determine which ones should be incorporated into Zapier’s shared platform.

Requirements

• 7+ years of experience in software engineering, with at least 3 years dedicated to building distributed, scalable, cloud-based ML/AI systems in production environments.
• At least 2 years of experience in LLM Ops, ML Ops, or adjacent platform/infrastructure work.
• Experience building shared services, internal platforms, or reusable developer tooling that enable other teams to move faster.
• Experience working through the full lifecycle of building, testing, deploying, and scaling ML/LLM architectures.
• Experience building with cloud infrastructure technologies.
• Comfort with typed languages and modern backend practices (mostly TypeScript & Python).

Nice-to-Haves

• Experience in TypeScript & Python.