At Zapier, we build and use automation every day to make work more efficient, creative, and human. So if you’re using AI tools while applying here – that’s great! We just ask that you use them responsibly and transparently.
Check out our guidance on How to Collaborate with AI During Zapier’s Hiring Process, including how to use AI tools like ChatGPT, Claude, Gemini, or others during our hiring process – and when not to.
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. You’ll help define 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!
If you’re interested in advancing your career at a fast-growing, profitable, impact-driven company, then read on…
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 have 7+ years of experience in software engineering, with at least 3 of those years dedicated to building distributed, scalable, cloud-based ML/AI systems in production environments. You have strong communication skills, sound engineering judgment, and a track record of building reliable systems that other engineers depend on.
You have at least 2 years of experience in LLM Ops, ML Ops, or adjacent platform/infrastructure work. You’re excited by problems like model access, inference reliability, observability, experiment management, evaluations, deployment workflows, governance, and production monitoring.
You have experience building shared services, internal platforms, or reusable developer tooling that enable other teams to move faster. You enjoy creating strong abstractions, reducing duplication, and improving standards across an organization.
You have experience of working through the full lifecycle of building, testing, deploying, and scaling ML/ LLM architectures.
You can identify and document trade-offs made during the development of AI/ML systems. You also have experience building with cloud infrastructure technologies.
You love enabling others. You’re energized by building infrastructure and tooling that make product engineers and ML practitioners more effective. You think deeply about developer experience and know that the best platforms are both powerful and easy to adopt.
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.
We believe all Zapiens should be rewarded competitively and equitably, using practices that are simple and transparent. This philosophy ensures we’re able to find, grow, and retain exceptional people from a broad range of backgrounds. Here’s how we define our compensation principles:
Standard:Â
Regular (Background Color): 
 VIP (Sticky & Broadcast in Email):
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