AI Backend Developer

AI BACKEND DEVELOPER – MADRID

We are looking for an AI Backend Developer with the drive and ability to be a key member of our young and versatile sports tech development team. We are a company that pioneers and develops new cutting-edge technologies – we would love for you to join our team and play your part in revolutionising the sports industry!

WHO ARE WE?

AIM Sport is at the forefront of the sports marketing industry. We currently work in over 500 football stadiums across the globe, providing fresh and innovative solutions to our fast-growing list of blue-chip clients. This elite portfolio includes the world’s biggest football clubs and commercial partners: FIFA, UEFA, Real Madrid CF, Paris Saint-Germain, Adidas, Audi, Heineken, Mastercard, and Sony to name just a few. We actively shape the digital revolution in sports marketing to drive the expansion and growth of our business as one of the top sports tech companies.

WHAT WILL YOU BE DOING?

You will design and build intelligent backend services that integrate AI and Large Language Models (LLMs) into our products. Your role focuses on developing Python-based REST APIs that combine AI-driven logic with deterministic, rule-based workflows to deliver scalable and production-ready solutions:

• Design, develop, and maintain Python backend services and RESTful APIs (FastAPI / Flask / Django REST)

• Build scalable, secure, and high-performance server-side architectures

• Integrate LLM and AI APIs (OpenAI, Azure OpenAI, Anthropic, Gemini, etc.) into backend workflows

• Design and implement prompt engineering strategies, orchestration layers, and AI pipelines

• Validate and structure AI outputs using Pydantic, JSON schemas, and post-processing logic

• Implement rule-based decision systems alongside AI-generated outputs

• Work with embeddings and vector databases (FAISS, Pinecone, Weaviate, or similar) when required

• Optimize database queries, caching layers, and data pipelines to support AI-driven features

• Implement async processing, background jobs, and task queues for long-running AI tasks

• Add logging, monitoring, and error handling for backend and AI workflows

• Collaborate with product, frontend, and QA teams to deliver AI-enabled functionality

• Troubleshoot production issues and perform root-cause analysis