AI Product Engineer

Learning a language can change a life by opening doors to new cultures, careers, and communities. Two billion people around the world are actively trying to learn a language, but the best way to learn (one-on-one tutoring) is hard to access at scale and hasn’t been meaningfully improved in decades. Speak is building a human-level, AI-powered tutor in your pocket: a conversation-first experience that lets learners actually speak, get instant feedback, and progress through carefully designed lessons. The result is a complete path from beginner to confident speaker across multiple languages.

Speak first launched in South Korea in 2019, where Speak has now become the number one language learning app, and we now serve learners across many markets and 15+ languages. Speak is one of the world’s leading AI companies, with over $150m raised in venture investment from OpenAI, Accel, Founders Fund, Khosla Ventures, and more, with a distributed team across San Francisco, Seoul, Tokyo, Taipei, and Ljubljana.

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.

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  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

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  Collaborating cross-functionally with other Engineering teams, Applied ML, Product, Design, and Content

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  Refining our process for building LLM apps, including best practices for prompting, experimentation/evaluation, LLM Ops, measuring quality and performance, etc.

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  Scaling existing product features to many more users and languages

• 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 LLM-powered capabilities and product experiences

• Ability to work independently and build at a high velocity

• San Francisco, CA