About LearnVector
For most of history, great teaching has been scarce. A brilliant teacher who knows you well, adapts to how you learn, and patiently stays with you until you get there — almost no one has had that. AI changes what's possible. LearnVector, founded by Andrew Ng, is building a trustworthy AI guide for learning, with a mission to accelerate human development. We're a small, fast-moving team working on-site in Mountain View, California and backed by a $100 million investment from Coursera.
About the role
The AI Engineer will build the agentic systems at the core of the product: 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 is not a wrap-an-API role. The hard problems are the ones frontier models don't solve on their own: 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 rather than merely pleasant, and verifying that generated teaching is correct before a learner ever sees it. You'll own systems end to end — design, implementation, evaluation, and iteration against real learner data.
What you will do
- 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 you bring
- 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
What success looks like
In your first 30 days, you will have shipped a measurable improvement to the core tutoring loop and stood up an evaluation that tells us whether it worked.
In your first 6 months, the agentic core — learner model, planning, verification — will be a durable system the whole product builds on, with quality metrics the team trusts and a cadence of improvement driven by real learner data.
Equal opportunity
LearnVector is committed to a workplace of mutual respect and equal opportunity. We hire based on qualifications, merit, and business needs, and do not discriminate on the basis of any characteristic protected by applicable law.
Accommodations
If you need a reasonable accommodation at any point in the application or interview process, we'll work with you. Requests are kept confidential and separate from hiring decisions.
Skills Required
- At least 3 years of software engineering experience
- Substantial hands-on experience building with LLM APIs such as Claude, OpenAI, or similar
- Experience with agentic workflows, tool use, structured output, long-context systems, and memory patterns
- Experience shipping and operating LLM systems in production
- Experience evaluating production LLM systems and building evaluation harnesses
- Strong Python and/or TypeScript/Node.js engineering skills
- Ability to own services end to end
- Ability to translate ambiguous product questions into measurable systems and work independently
- Experience with conversational AI products, tutoring systems, or long-running assistant relationships
- Background in recommendation, personalization, or user-modeling systems
- Familiarity with education or learning science
- Experience with voice interfaces or real-time interaction
AI Fund Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about AI Fund and has not been reviewed or approved by AI Fund.
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Healthcare Strength — Health coverage is portrayed as strong with great healthcare and dental coverage, plus vision insurance, long-term disability, and life insurance. Feedback suggests this aligns with tech-standard benefits for US roles at a small venture studio.
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Retirement Support — Retirement benefits include a 401(k) plan with employer match for US employees. Feedback suggests this forms part of a competitive total package for fund roles.
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Parental & Family Support — Family support includes fully paid parental leave for applicable roles. Feedback suggests this is a standout benefit for an organization of this size.
AI Fund Insights
What We Do
Who is AI Fund? We are a team of AI pioneers, proven entrepreneurs, seasoned operators, and venture capitalists that collaborates with leading entrepreneurs to solve big challenges using artificial intelligence. Founded in 2017 by Dr. Andrew Ng, AI Fund is backed with $176 million in capital by some of the leading VC firms and investors, including NEA, Sequoia, and Greylock. How Are We Different? We work with entrepreneurs during their startup’s most critical and risky phase, from 0 to 1. At the earliest stages, your company strategy is still being formed, and you’re still on the path to demonstrating your idea’s full potential – this is a reality we understand. This is the period when decisions on product strategy, market fit, and team are most critical, moving fast and fixing parts of your business when you have limited resources is a challenge. We believe the best way to help entrepreneurs is by providing our time, expertise, and resources to help flesh out these key strategic decisions. Making the right decisions at the right time can often make the difference. We are here to improve these dynamics, at a time when the help matters the most. Why Work With AI Fund? Getting a startup from idea to Series A funding is not easy. We’ve been there and understand the challenges you must overcome. Whether you desire limited help and just want access to our unique ecosystems of AI experts and entrepreneurs or you would like our full support, we are interested in the opportunity to help in your success. We are flexible in how we work with companies, but ultimately, we are here to maximize your chance of success and accelerate getting your company to market. We provide the capital, expertise, and resources to accelerate the work required to minimize risks in your startup, help you rise above the noise, and make your company more attractive to new investors.
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