NodeJS (Node.js)
JavascriptCore AI Backend Engineer – LLM Fine-Tuning
You know that moment when you don’t just debug code — you train a model, fine-tune it, and suddenly it understands your domain better than you expected? That’s the kind of magic we’re looking for.
We’re building something that turns chaotic social video data into crystal-clear business intelligence. Not just another API — but AI-backed architecture fine-tuned to our world. Systems that marketing teams thank you for, because they feel the intelligence, not just the infrastructure.
Either you feel the craft when you read this, or you don’t. This isn’t just another backend role. This is where you bring together scalable systems and cutting-edge LLMs to build something the world hasn’t seen before.
Who We Are
We’re a small, global team that ships fast. Every line of code and every model choice affects millions of video analysis requests.
Our engineers don’t just build APIs — they architect solutions, they optimize at scale, and now, they fine-tune models to make AI work in the real world. Our CPTO still codes. Our senior engineers make complexity look effortless. Our backend team sets a standard that others ask how we move so fast.
What We Need
We need someone who’s lived both sides of this life:
- Backend excellence: building high-scale, high-performance systems.
- LLM fine-tuning: hands-on with open-source models, not just calling APIs.
Someone who can sit with a requirement at 2pm and by 6pm not only has endpoints working, but also has a fine-tuned model running behind them — customized to our use case.
Your Craft
- JavaScript/TypeScript & NodeJS as core backend tools.
- Next.js for full-stack where needed.
- Rust when performance is non-negotiable.
- Golang/Python as comfortable tools of choice.
- MySQL/Postgres/Redis — wielded with intention.
- AWS ecosystem — your playground, not your puzzle.
- LLM/AI integration you’ve actually shipped.
- Open-source LLM fine-tuning experience:
- Bringing in open-source models (LLaMA, Mistral, Falcon, etc.).
- Fine-tuning/adapting them for specific domains.
- Optimizing for inference cost, latency, and accuracy.
The Reality
The work is beautifully complex. The scale is real and growing. The problems are the kind that wake you up at 3am with solutions.
If you get your energy from building backend systems and adapting LLMs to make them smarter for real-world use, you’ll probably fall in love with what we do. If you’re only interested in APIs without touching models, this won’t be your thing — and that’s completely okay.
How to Apply
If you’re reading this thinking “finally, a team that actually cares about real AI engineering” — we’d love to see something you’ve built.
Not just a resume. Show us your craft:
- An LLM fine-tuning repo.
- A domain-adapted model you worked on.
- A system design where you combined backend and AI.
- Or even a short write-up or voice note explaining what you’ve fine-tuned.
We’re genuinely excited to see what you’ve done and have a meaningful conversation about whether this could be magic for both of us.
Shubham Vishwakarma
Full Stack Developer - Averlon
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Follow CutshortShubham Vishwakarma
Full Stack Developer - Averlon