Founding Volunteer10–20 hoursRemote · worldwide

AI Engineer

Work on the technical core of Regent — full-stack engineering plus integrating AI models into our backend, designing algorithms that generate good content, building new features, and improving existing ones. We need coders who ship working code.

1-month minimum commitment

Every founding volunteer commits to at least one month of consistent work. The longer you stay, the more experience you walk away with — and the closer we get to funding, where you become a paid hire first.

About the role

AI Engineer at Regent is where the substance of the product lives. You will work across the entire stack — frontend (Next.js, TypeScript, Tailwind, motion), backend (Node.js REST APIs, database, queueing), and the AI layer where we integrate open-source models into production pipelines. Research is welcome — we read papers and prototype constantly — but the bar is shipping code that runs in production.

If you can read a paper, distill the idea, and turn it into a feature that ships to real users in the same week, this is your role. If you only want to write notebooks and call it done, this is not.

What you'll do

Ship full-stack features end-to-end — frontend, backend, and the AI inference layer.
Integrate new open-source AI models into the Regent backend and test them at production scale.
Design and refine the algorithms that decide what content Regent generates and how.
Build reliability into the agent and pipeline layer — failure recovery, retries, queueing.
Performance and cost engineering on the inference stack.
Ship new features and improve existing ones based on real user signal.
Research, prototype, and turn ideas into production code that works at scale.

Required

What we look for

Strong full-stack engineering. You can own a feature from UI to database to inference and back.
Frontend: TypeScript, JavaScript, React, Next.js, Tailwind CSS, animation libraries (Framer Motion or equivalent).
Backend: Node.js REST API design, Postgres, async job processing, file storage.
AI/ML fundamentals — comfortable working with open-source models, integrating them into production code, and tuning them on real data.
Algorithmic thinking — you can design the logic behind a content generation pipeline, not just wire APIs together.
Research mindset paired with shipping discipline — read papers, prototype, deliver working code.
Production instincts. Your code runs reliably. You debug under load. You measure before you optimize.

Nice to have

Bonus skills

Experience integrating open-source generative models into production systems.
Familiarity with running models on consumer GPUs or serverless GPU platforms.
Open-source contributions on AI infrastructure.
Comfort with Cloudflare R2 / S3, Supabase, Clerk, or similar primitives.

What you'll get out of this

Hands-on work on a multi-modal AI agent system in production.
Full-stack shipping experience across modern web + AI infrastructure.
Direct ownership of features that real users depend on.
Reference letter + portfolio output for senior engineering roles after Regent raises.

Frequently asked

What stack do you use?+

Frontend: Next.js + TypeScript + Tailwind. Backend: Node.js + Postgres + Clerk for auth. AI: open-source generative models integrated into our pipeline. Infra: Vercel + Cloudflare R2 + GPU compute.

Do I need to know all of frontend + backend + AI?+

Strongest across all three is ideal. If you are deep on one and solid on the others, apply anyway — show us the work.

Is this a research role?+

No. Research is part of the job, but the deliverable is always working production code. We need coders who can do research, not researchers who avoid shipping.

Is this paid?+

No, but with the strongest priority-for-paid-hire commitment of any role. If we raise, the engineering team is the first hired.

Apply now

Ready to build with us?
Send your application.

We review every application personally and get back within 5 business days.

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