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Nectir is the secure AI infrastructure purpose-built for schools. Nectir AI provides 24/7 personalized learning support grounded in course content, without compromising trust, outcomes, or academic integrity. Nectir AI can be integrated into existing Learning Management Systems and is fully FERPA- and SOC 2-compliant. Trusted by 80,000 students across 100+ campuses, Nectir is backed by independent, peer-reviewed research demonstrating a 7.5% campuswide GPA increase. Nectir has raised $18.5M from leading investors including Rethink Impact, Long Journey Ventures, and Entrada Ventures.
Our mission is to build a personalized learning experience for every student in the world. The AI engineer's work sits at the heart of that: making sure every interaction is high quality, grounded in the right context, and accurate across the subjects students actually study, from language and math to science and the humanities. It's the difference between an AI that can answer a question and an AI that can genuinely help someone learn.
We're looking for our first full-time AI engineer. You'll be the trailblazer on this side of the stack, with real ownership over where our AI systems go next. Day-to-day, that means designing and iterating on how our AI thinks, responds, and retains context, building evaluations rigorous enough to catch regressions before users do, and turning new model releases into shipped capabilities. You're also a strong full-stack developer, so when an AI feature needs to ship end-to-end across the platform, you can take it there yourself.
You'll report directly to Jordan Long, CTO, and partner closely with product, engineering, data, and customer success.
AI Systems and Agent Infrastructure
Own the direction of the AI that powers Nectir: how it thinks, what context it sees, what it remembers, and how it uses tools.
Design and iterate on prompts, context, retrieval, and memory across the product.
Build evaluations (golden answers, traces, production monitoring) rigorous enough to catch regressions before users do.
LLM Engineering
Work across frontier models from the major providers to pick the right model for the right job, and tune cost, latency, and quality across that mix.
Build the multi-agent patterns and tooling that let us scale AI capability as the surface area grows.
Turn new model releases and new techniques into shipped improvements quickly.
Full-Stack AI Features
Ship AI-facing features end to end when they need to land in the product.
Partner with the full-stack team to cleanly integrate AI capabilities into the platform.
Own the end-to-end quality of the AI experience our users actually see.
Frontier and Craft
Track what ships across the AI ecosystem and translate it into real improvements in our product.
Share what you learn and raise the bar for what the rest of the team thinks is possible.
Must-Haves
Direct experience building with LLMs in production, not just prototyping. You've shipped features that real users relied on.
Strong grasp of prompting, context engineering, retrieval, evaluation, and the practical realities of working with frontier models.
Proficiency in TypeScript and strong full-stack engineering fundamentals. Our entire stack is TypeScript.
Rigor around evaluation: you measure AI quality with real data, not vibes.
Product mindset: you build for real users, not just for the model. You can tell when an output is good enough to ship and when it isn't.
Proactive, self-directed communication in a remote, async environment.
Nice-to-Haves
Experience with multi-agent systems, long-running agents, or memory architectures.
Familiarity with background workers and durable job processing.
A track record outside of day jobs: a company you started, an open-source project you maintain, or side projects you keep shipping.
Deep passion for AI, or a real connection to education.
Background in edtech or higher education.
No degree requirements. What you know and can do is more important than where you learned it.
We're a startup, which means the work moves fast, but the impact is real. You will not be a small cog in a big machine here, but the one building the machine itself.
This is a full-time, remote position, open globally. You should be comfortable working with meaningful overlap with US business hours.
Our mission is to build a personalized learning experience for every student in the world. The AI engineer's work sits at the heart of that: ensuring every interaction is high-quality, grounded in the right context, and accurate across the subjects students actually study, from language and math to science and the humanities. It's the difference between an AI that can answer a question and an AI that can genuinely help someone learn.
Competitive base salary
Comprehensive health coverage: medical, dental, and vision (for US-based roles only)
401k with employer match (for US-based roles only)
Equity (stock options), so you share in what we're building
Flexible, remote-first work environment
Please include a link to your GitHub, a portfolio of past projects, or a brief description of a technical challenge you've solved recently. We care about how you think through problems, not just what languages you know.
After you apply, unlock the direct contact details of the people who actually make the call. A quick follow-up makes you 5x more likely to land an interview.
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