Founding Tech Member (AI / Full-Stack)

Equity-first | No salary initially | Remote / Flexible

Strong plus: You actively read fiction books.

About the Project

Celsius 233 operates in the book publishing ecosystem, building AI-powered, fully automated pipelines.

The project has been selected into an early-stage startup accelerator program and is currently in its build and expansion phase. Funding is expected at a later stage based on progress.

The company already runs live production infrastructure with real users. New intelligence-driven product layers are now under active development.

The Role

This is a founding technical role with real ownership and responsibility.

You'll work across:

LLM-based systems

Backend services and APIs

Frontend interfaces

AI-driven automation pipelines

You'll collaborate directly with the founder and help shape both the technical architecture and the direction of new product layers.

What You'll Actually Do

Build and iterate on LLM-powered workflows

Design, improve, and scale automated AI pipelines

Work fluidly across frontend and backend

Improve performance, reliability, and maintainability of live systems

Turn loosely defined ideas into shipped, working features

This is a hands-on, execution-heavy role.

Who This Is For

You're a strong fit if you:

Have 13 years of hands-on development experience

Can adapt across LLMs, backend, and frontend

Have shipped real systems (not just tutorials)

Read fiction regularly or have strong interest in it

Want ownership, learning, and long-term upside

Tech Stack (indicative, not rigid)

Python

LLM APIs / open models

Backend frameworks and databases

Basic frontend (enough to ship usable interfaces)

Automation, orchestration, deployment

Tooling matters less than execution speed and adaptability.

Compensation

Equity-first (founding-level contribution expected)

No salary initially

Clear transition to paid role post-funding

Long-term ownership in what you build

Why Join

Selected into an accelerator program

Live AI-powered pipelines and production systems

Direct influence over architecture and product direction

Build in a domain most AI teams overlook: books