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AI Product Engineer

In office • San Francisco💼 Full-time🗓 2026-06-24

Core

Developing and deploying LLM-powered language learning products and features for millions of users globally.

Role type

Full-stack AI Product Engineer

Builds

Conversational onboarding, lesson experiences, grammatical assessment, and personalized lessons

Domain

EdTech / Language Learning / Generative AI

Deliverable

product features

Required skills

Full stack/backend engineering, React, Node, TypeScript, Python, LLM app development, LLM Ops, vector databases, RAG, prompt engineering

Preferred skills

Product intuition, cross-functional collaboration

Technologies

React, Node, TypeScript, Python, vector databases, RAG

Responsibilities

Develop and deploy LLM-powered language learning products across the full stack; Enhance quality and performance of existing AI-powered features; Refine processes for building LLM apps including prompting and evaluation; Scale product features to more users and languages

Seniority

Mid-level, hands-on IC

Rewrite
## About the role As an AI Product Engineer at Speak, you'll play a pivotal role in developing the future of language learning and creating the most effective path to language fluency. Your primary responsibility will be developing innovative product experiences powered by Language Learning Models (LLMs) and deploying them to millions of users. Your tasks will span the full stack and beyond, from evaluating models and testing prompts to developing and iterating on various product features such as our conversational onboarding and lesson experiences, grammatical assessment and feedback, and personalized lessons. We're constantly pushing the boundaries of what LLMs can do to provide an exceptional and unparalleled language learning experience to users in over 30 countries worldwide. ## Responsibilities - Developing and deploying LLM-powered language learning products across the full stack, as well as enhancing the quality and performance of existing AI-powered features within Speak - Collaborating cross-functionally with other Engineering teams, Applied ML, Product, Design, and Content - Refining our process for building LLM apps, including best practices for prompting, experimentation/evaluation, LLM Ops, measuring quality and performance, etc. - Scaling existing product features to many more users and languages ## Requirements - 3-5+ years of experience in full stack/backend, product-focused software engineering - Proficiency in React/Node/Typescript and Python - You have real-world experience developing and deploying LLM apps and a strong understanding, gained through experience, of what works and what doesn't - A keen intuition for improving performance and output quality of LLM systems - Experience with LLM Ops and tools (e.g., vector databases, RAG, prompt ops) - Strong product intuition — the ability to think broadly and cross-functionally about innovative
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