Full Stack Engineer

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 LLM→SQL 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, NL→SQL, 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.