About the job
Our mission is to become the operational backbone for modern commerce, empowering brands—from design partners to mid-market retailers to own their customer relationships through intelligent, multimodal AI agents. We leverage Gemini to build a "flywheel" of sales and support capabilities that drive conversion and efficiency. In this role, you will build the foundational systems that allow these agents to scale globally, ensuring a rapid, "out-of-the-box" onboarding experience for merchants and enabling a seamless headless implementation for those who prefer to own the user experience (UX). Applied AI builds conversational agents deployed at a large scale that achieve very meaningful results in the real world.
Responsibilities
Build self-service tooling and automated evaluation frameworks.
Architect and refine unified, scalable Application Programming Interfaces (APIs) for critical functions like catalog ingestion (e.g., Universal Commerce Protocol), real-time agent configuration, and "one-line Software Development Kit (SDK)" site integration.
Design infrastructure that shrinks the onboarding gap, enabling rapid deployment for a global customer base ranging from large enterprises to e-commerce merchants.
Drive the feature lifecycle from experimentation to production, ensuring high reliability for shopping journeys that combine search, business, and support.
Utilize Large Language Model (LLM) simulators and judges to continuously monitor performance, manage quality hill-climbing, and prevent regressions.
Qualifications
Minimum
Bachelor’s degree or equivalent practical experience.
5 years of experience with software development in one or more programming languages.
3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
3 years of experience with one or more of the following: speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
Preferred
Experience building and scaling platform infrastructure for SaaS or e-commerce products.
Experience in a technical leadership role leading project teams and setting technical direction.
Experience in product sense with a focus on developer experience (DX) and merchant tooling, ensuring features directly address customer pain points.
Ability to work in an agile, "0-to-1" environment, managing projects from conception to launch.