AI Data Engineer | Mid-Senior | Python

We are building a world-class, AI-driven B2B analytics SaaS. Built from scratch as a core product, it defines a new generation of marketing analytics within Tesonet Group.

You’ll join while core architecture, data flows, and engineering principles are actively being designed, with the opportunity to take real ownership and shape how the product is built and how teams collaborate.

The platform is built around intelligent automation, real-time data processing, ML and large-scale distributed systems, with AI deeply embedded at its core. By working with complex data, we deliver a powerful self-service analytics experience that enables faster, smarter marketing decisions.

Main Responsibilities

• Build and shape tomorrow’s AI-based application, ensure scalable data and AI pipelines.
• Play with cutting-edge AI tech, prototyping and experimenting with LLMs (APIs, RAG, embeddings, etc.) to elevate accuracy, insight quality, and product impact.
• Turn data into value by preparing, transforming, and managing datasets that power models, features and production systems.
• Work closely with different teams to get things done together, partnering with product, data science and engineering to uncover smart AI opportunities and launch them into real use.
• Fine-tune our systems and existing LLMs for excellence, create and optimize prompts, workflows, and model interactions for performance and reliability.
• Own quality and scale by ensuring observability, robustness, and smooth operation across distributed data + AI systems.

Core requirements

• Proven experience writing clean, reliable Python code for data processing, automation, and transformation.
• Strong understanding of data engineering fundamentals: ETL/ELT workflows, orchestrating jobs (e.g., Airflow), building and querying data warehouses (e.g., BigQuery), using version control, CI/CD and Docker containers effectively.
• Optional experience training your own machine learning models using frameworks such as TensorFlow, PyTorch, scikit-learn, Keras or similar tools. 
• Optional experience in fine-tuning existing LLM models.
• Comfort working across data plumbing and AI/model workflows, with the ability to switch between the two effectively.
• Familiarity with tools like dbt, Kafka or other streaming systems and observability tooling (logs, metrics, tracing) is a plus.
• A curious, fast-moving mindset with the ability to prototype quickly, learn new tech fast, and share knowledge with others.

Salary

Gross salary 4500 - 7100 Eur per month.

We are open to discussing a different salary based on your skills, experience, and potential impact.

Thank you for your application.

We appreciate your interest in joining our team. Please note that only selected candidates will be contacted.