Zapier is seeking a Sr. Applied AI Engineer to join their Data AI/ML team.
The role involves building the AI foundation that powers product experiences at Zapier.
Responsibilities include designing and building reusable building blocks such as LLM-powered APIs, vector search services, orchestration libraries, and evaluation tooling.
The engineer will collaborate with AI Engineers, Product teams, and Machine Learning Engineers to ensure AI capabilities are scalable, reliable, and user-friendly.
The position offers the opportunity to shape AI implementation from raw data and infrastructure to user-facing product experiences.
The role is remote and open to candidates in the Americas and EMEA.
Requirements:
Candidates must have 7+ years of experience in software engineering, with at least 5 years focused on building distributed, scalable cloud-based web applications.
A minimum of 1 year of experience working with large language models (LLMs) in production environments is required.
Familiarity with technologies such as transformer networks and attention mechanisms is essential.
Experience deploying evaluation frameworks for LLMs, including performance, reliability, and bias assessment, is preferred.
Knowledge of Retrieval-Augmented Generation (RAG) systems and optimization strategies for knowledge retrieval is important.
Candidates should have experience with the full lifecycle of building, testing, deploying, and scaling LLM architectures.
The ability to identify and document trade-offs made during development is necessary.
Experience with cloud infrastructure technologies is required.
A passion for delivering customer-focused solutions and embodying Zapier's values is essential.
Benefits:
Zapier offers a flexible remote work environment that promotes work-life balance.
Employees have the opportunity to work with cutting-edge technology and collaborate with talented individuals.
The company is committed to diversity, inclusion, and equity in the workplace.
Zapier provides a supportive culture that values different perspectives and experiences.
Employees can expect a transparent application process with timely communication regarding their application status.
