AI Engineer

career • Mountain View, CA

60d • Onsite

About The Position

LearnVector is building a trustworthy AI guide for learning, with a mission to accelerate human development. Founded by Andrew Ng, the company is backed by a $100 million investment from Coursera. The AI Engineer will build the agentic systems at the core of the product, which are systems that understand each learner, plan a path with them toward skills worth having, and work with them step by step until they get there. This role involves tackling hard problems that frontier models don't solve on their own, such as maintaining an accurate picture of a learner over weeks and months, deciding what to teach next and when to hold back, keeping long-running conversations useful, and verifying generated teaching is correct before a learner sees it. The engineer will own systems end to end, including design, implementation, evaluation, and iteration against real learner data.

Requirements

• AI-native: you default to AI-assisted coding and building agentic automations in everything you do, you have an appetite for and record of experimenting with the newest AI engineering practices
• 3+ years as a software engineer, with substantial hands-on experience building with LLM APIs (Claude, OpenAI, or similar): agentic workflows, tool use, structured output, long-context and memory patterns
• Experience shipping and operating LLM systems in production, including evaluating them - you have opinions about evals because you've built them
• Strong Python and/or TypeScript/Node engineering skills; comfort owning services end to end
• Ability to turn a fuzzy product question ("is the tutor actually helping?") into a measurable system, and ship without heavy oversight

Nice To Haves

• Experience with conversational AI products, tutoring systems, or long-running assistant relationships
• Background in recommendation, personalization, or user-modeling systems
• Familiarity with the education or learning-science landscape
• Experience with voice interfaces or real-time interaction

Responsibilities

• Design and build the agentic core: multi-step tutoring loops, tool use, memory, and planning over long-horizon learner relationships
• Build the learner model — the evolving, evidence-backed representation of what each learner knows, wants, and responds to — and the systems that read and write it
• Build evaluation harnesses for conversational quality and teaching quality, and use them to drive iteration; define what "this session taught something" means operationally and measure it
• Design guardrails and verification layers so generated content and tutor claims meet a bar a trusted brand requires
• Work daily with the founding team, including Andrew, on the hardest product questions: what should an AI tutor do, and how do we know it's working?

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: No Education Listed