Be part of nolas workspace

AI Developer (m/f/d)

We have a clear goal: nolas will be THE infrastructure software for organizational processes in Europe over the next ten years. With nolas, we enable organizations to save up to 40% of their administrative costs. Not through individual tools, but through a new operating system for organizational processes.

nolas acts as an operating system into which companies can plug in their individual workflows. Universally applicable: from hospitals to the housing industry to authorities.

Successful digitization is never just technology. It always starts with people, processes and decisions. And that's where you come in.

Your role in the team:

As an AI developer at nolas, you develop intelligent functions for our operating system to control organizational processes. You have experience from real organizational and software contexts and understand how users, workflows and document processes actually work. On this basis, you will develop AI-based solutions that support decisions, extract data from documents and efficiently automate processes.

In concrete terms, this means:

Agentic systems: You develop AI agents and intelligent applications (e.g. LLM-based and agentic systems) — from idea to productive use.

Multimodal pipelines: You develop multimodal pipelines for document classification and data extraction. You cover the entire process — from classification to structured data extraction with spatially sensitive models.

Sovereign AI: You implement and optimize self-hosted LLMs (especially Mistral and other open-weights models) to ensure data sovereignty and high performance.

Advanced RAG: You develop retrieval-augmented generation (RAG) architectures for efficient data queries and context-based reasoning across multiple clients.

Inference architecture: You select the appropriate frameworks and components to ensure the performance and scalability of our entire inference architecture.

MLOps & Reliability: You're not working on the “deploy and forget” principle. You develop infrastructure to monitor agent reasoning, identify changes in document layouts and ensure an extraction accuracy of 99.9%.

This is what you ideally bring with you:

Technology & development

GenAI & Document Intelligence: Profound knowledge and practical experience in software development as well as experience with generative AI, NLP and data-driven projects in the context of real organizational and document processes. You are familiar with Visual Document Understanding (VDU), such as LayoutLM and OCR and Vision libraries such as DocTR.

Data science & analysis: You can analyze large amounts of data, recognize connections, and develop predictive models to solve complex organizational problems.

Polyglot developer: Very good knowledge of Python is a prerequisite. Experience with other languages such as Java, TypeScript or Go is an advantage.

System architecture: Experience in building and operating REST APIs, vector databases and relational databases as well as in integrating and optimizing models in scalable applications.

projects: You've already worked on real projects and delivered results.

Data & AI models

Model serving & optimization: Experience deploying and scaling models with vLLM and Triton Inference Server.

Data analysis: You can analyze, structure and prepare large amounts of data for training and development.

Extraction techniques: Experience with hybrid extraction methods that combine DocTR for text and layout recognition and LLMs (e.g. Mistral) for semantic understanding.

Scalable AI systems: Experience deploying models in cloud or production environments, with a focus on multi-tenant security and performance

Data life cycle: You can analyze, clean, and structure large, unstructured data sets — for training, fine-tuning, and evaluation.

Our tech stack

programming languages: Python (primary), Java, TypeScript

Inference & Serving: vLLM, NVIDIA Triton Inference Server

models: Mistral (LLM), LayoutLM (VDU), DocTR (OCR), LSTM, Transformers, Vision Transformer (ViT)

Frameworks: Scikit-learn, pandas, XGBoost, LangChain, llamaIndex

infrastructure: Self-hosted AI pipelines, REST APIs, vector stores

Other technologies: Kafka, Object Storage, WebSockets

What to expect at Nolas

Develop AI solutions that solve real problems and are used productively

Help shape technologies, models and applications from idea to product

Quick decisions, high speed and clear responsibilities

An ambitious team with vision, substance and a strong desire to implement

Please include links to your GitHub, portfolio, or other relevant projects in your application.

No benefits bingo.

No kicker, no work-life balance. Simply support your growth within a powerful team.

Skills get you in.
Personality moves you forward.
What you get depends on what you make of it.