Full Stack Engineer (Python / TypeScript) - AI Products

MAindTec GmbH
Ingolstadt, Germany
3 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Amazon Web Services Microsoft Azure Cloud Computing Content Analysis Continuous Integration Database Schema Django Web Framework High-Level Architecture Python (Programming Language) PostgreSQL Software Architecture
+17 more
Queueing Systems Redis Tensorflow Next.js Software Engineering TypeScript WebSocket Pytorch ReactJS Flask (Web Framework) Large Language Models Deep Learning Backend Fastapi HuggingFace Api Design Docker

Job description

At MAindTec we build AI-powered products across two areas: document analysis and engineering. We’re hiring a Full Stack Engineer to own features end-to-end - from database schema to production UI, from first prototype to shipped feature. Small team, fast cycles, real users. You’ll have meaningful ownership from week one.

Requirements

Do you have experience in TypeScript?, Do you have a Master’s degree?, Production full-stack experience - you’ve shipped systems people depend on

  • Strong CS fundamentals: software architecture and API design (REST, SSE, WebSockets)

  • Python backend (FastAPI, Django, or Flask) with comfort in async patterns

  • TypeScript with Next.js / React - SSR/SSG, state management, thoughtful component design

  • PostgreSQL: schema design and migration tooling (Alembic or similar)

  • Docker, CI/CD, and cloud deployment on Azure, AWS, or GCP

  • Working understanding of deep learning - model architectures, training and inference workflows, and how to wire models into production

  • Bachelor’s or Master’s in CS / Software Engineering - or self-taught with a portfolio that speaks for itself

  • Clear communicator who can translate technical work for non-technical audiences

Nice to have

  • Hands-on LLM integration (OpenAI, Anthropic)

  • Vector databases (pgvector, Pinecone) and RAG architectures

  • PyTorch, TensorFlow, or Hugging Face experience

  • Redis, message queues, or background worker systems

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