Тип вакансії: Повна зайнятість

Розташування:

Зарплата: $3500–$5000

We're an early-stage product company building an AI-powered analytics platform for the iGaming industry. Users get answers from their data in plain English an LLM turns questions into validated SQL over a large data warehouse alongside a set of analytics dashboards and data pipelines. It's live in production.
You'd be our first dedicated engineer, working directly with a technical founder (product) and an experienced CTO (architecture + code review) with a real path to Tech Lead as the team grows. You won't be flying solo, and you'll help shape the architecture, not just maintain it.

What you'll do

Build and ship features across the backend and the dashboard.
Write correct, performant SQL against a large Postgres warehouse the numbers drive real decisions.
Extend the LLMSQL pipeline and the analytics APIs behind the product.
Own reliability, testing, and deploy stability as we scale.
Maintain and extend the React / TypeScript front end.

Stack

Backend: Python 3.12 + FastAPI (async, SQL-first with asyncpg no ORM).
Data: large Azure PostgreSQL warehouse (tens of millions of rows) + nightly aggregation pipelines.
AI: Anthropic Claude (natural-language SQL, agent workflows).
Frontend: React 18 + TypeScript + Vite, shadcn/ui + Tailwind, TanStack Query, Recharts.
Infra: Azure, Redis, Docker, GitHub Actions.
Note: the data-science/ML models are owned by the founder you won't build or maintain those.

You'll thrive here if you have

Strong SQL and relational-DB skills (Postgres a plus) the single most important thing.
Solid Python, ideally with an async framework (FastAPI).
Good React + TypeScript.
A correctness-first instinct for data, and the ability to pick up a fast-built codebase and make it solid.
Comfort with cloud + CI/CD (Azure a plus) and Docker.

Nice to have

LLM app experience (Anthropic/OpenAI, NLSQL, RAG).
Data engineering / BI / warehousing background.
iGaming, fintech, or marketplace domain experience.

Why join

A live, revenue-generating product early enough to shape it.
A clear growth path to Tech Lead.
Modern stack: large data warehouse + production LLM pipeline + polished React app.
Real support: a technical founder on product, an experienced CTO on engineering.

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