[Hiring] Sr. Applied AI Engineer @Zapier

Role Description

Are you excited about building the platform that makes AI and machine learning development faster, safer, and more reliable across an entire company? We’re thrilled to invite you to join Zapier’s AI Platform team as a Sr. Applied AI Engineer!

As a key member of this team, you’ll help build and evolve the shared infrastructure that powers AI and ML development across Zapier. The AI Platform team owns the common foundations that product and engineering teams rely on when building with machine learning and generative AI - including systems like our LLM proxy server, observability tooling, and ML Ops platform capabilities.

This is a highly leveraged role. Rather than building a single end-user feature, you’ll create the core systems, tooling, and standards that many teams use as their baseline for shipping intelligent products and internal AI-powered workflows. You’ll work at the intersection of platform engineering, applied AI, and developer experience to make it easier for teams across Zapier 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.
• Defining the paved road for teams building with AI at Zapier.

If you’re passionate about large language models & machine learning, developer platforms, operational excellence, and building the systems that make AI usable at scale, we’d love to meet you!

Qualifications

• 7+ years of experience in software engineering.
• At least 3 years dedicated to building distributed, scalable, cloud-based ML/AI systems in production environments.
• Strong communication skills and sound engineering judgment.
• Track record of building reliable systems that other engineers depend on.
• 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.
• Experience working through the full lifecycle of building, testing, deploying, and scaling ML/LLM architectures.
• Ability to identify and document trade-offs made during the development of AI/ML systems.
• Experience building with cloud infrastructure technologies.
• Passion for enabling others and improving developer experience.

Requirements

• Experience in TypeScript & Python (experience is a plus, but comfort with typed languages and modern backend practices is a must).
• Ability to proactively identify tooling gaps and standardize best practices for building, deploying, and monitoring AI-driven experiences.
• Collaborate closely with engineers across product, infra, and data teams.
• Evaluate emerging tools, models, and patterns in the AI ecosystem.

Benefits

• Opportunity to work in a fast-growing, profitable, impact-driven company.

Application Deadline

The anticipated application window is 30 days from the date job is posted, unless the number of applicants requires it to close sooner or later, or if the position is filled.