AI Engineer
Mountain View, CA • Full time
Posted 2mo ago
Job Location
Mountain View, CA
Tech Stack
Remote Work Policy
On-site
Employment Type
Full time
Categories
AI Agent Engineer
About the job
LearnVector, founded by Andrew Ng, is building a trustworthy AI guide for learning with the mission to accelerate human development. We are a small, fast-moving team working on-site in Mountain View, California, backed by a $100 million investment from Coursera. The AI Engineer will build the agentic systems at the core of the product, focusing on systems that understand each learner, plan a path toward valuable skills, and guide them step-by-step. This role involves tackling complex challenges beyond frontier models, such as maintaining learner profiles over time, optimizing teaching strategies, ensuring long-running conversations are useful, and verifying the accuracy of generated content before it reaches the learner. You will own these systems end-to-end, including design, implementation, evaluation, and iteration based on real learner data.
Responsibilities
- Design and build the agentic core, including multi-step tutoring loops, tool use, memory, and planning for long-horizon learner relationships.
- Build and maintain the learner model, an evolving representation of learner knowledge, goals, and responses, along with the systems that interact with it.
- Develop and utilize evaluation harnesses for conversational and teaching quality to drive iteration and operationally define and measure learning.
- Design guardrails and verification layers to ensure generated content and tutor claims meet brand standards.
- Collaborate daily with the founding team on core product questions regarding AI tutor functionality and effectiveness measurement.
Requirements
- Default to AI-assisted coding and building agentic automations, with a record of experimenting with new AI engineering practices.
- Substantial hands-on experience building with LLM APIs (Claude, OpenAI, or similar), including agentic workflows, tool use, structured output, and long-context/memory patterns.
- Experience shipping and operating LLM systems in production, including evaluating them.
- Strong Python and/or TypeScript/Node engineering skills.
- Ability to own services end-to-end.
- Capacity to translate fuzzy product questions into measurable systems and ship independently.
- Experience with conversational AI products, tutoring systems, or long-running assistant relationships is a plus.
- Background in recommendation, personalization, or user-modeling systems is a plus.
- Familiarity with the education or learning-science landscape is a plus.
- Experience with voice interfaces or real-time interaction is a plus.