openashbyhqbvp
Applied AI Engineer
Zapier
LocationNAMER, EMEA
WorkplaceRemote
EmploymentFullTime
Posted2026-06-23T12:03:28.616+00:00
Last observed2026-06-29 00:42:46.715223
Job idbvp-zapier:ashbyhq:38434b88-086c-424b-8d18-8d006e0b71b8
AI AT ZAPIER At Zapier https://zapier.com/about, 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 https://zapier.com/l/jobs/ai-at-zapier, including how to use AI tools like ChatGPT, Claude, Gemini, or others during our hiring process - and when not to. Hi there! 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 an 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 systems, developer platforms, and building tools that help other engineers move faster, 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… - Our Commitment to Applicants https://zapier.com/jobs/our-commitment-to-applicants/ - Culture and Values at Zapier https://zapier.com/jobs/culture-and-values-at-zapier/ - Zapier Guide to Remote Work https://zapier.com/learn/remote-work/ - Zapier Code of Conduct https://zapier.com/jobs/zapier-code-of-conduct/ - Diversity and Inclusivity at Zapier https://zapier.com/jobs/working-on-diversity-and-inclusivity/ 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: ABOUT YOU 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 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 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 experience of working through the full lifecycle of building, testing, deploying, and scaling ML/ LLM architectures. 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 enjoy working collaboratively and learning from others. You’re excited to partner with more senior engineers and cross-functional teams to build reusab
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