Fullstack Applied AI Engineer; m​/f​/d

Since its foundation in 1925, the DEKRA promise has been to ensure the safety of human interaction with technology and the environment. The company currently employs around 52,000 people in more than 60 countries on all five continents. With qualified and independent expert services, they provide safety on the road, at work and at home.

We have a clear and ambitious vision of the future. The vision for our 100th birthday in 2025 is to see DEKRA as the global partner for a safe world.

On this ocassion, an exciting opportunity has arisen in our
Data & AI Engineering and Innovation Team
.

You want to know more? Here we go!

We are currently looking for a Full Stack Applied AI Engineer to strengthen our Data & AI Engineering and Innovation Team .

• Develop and maintain applications and services that make AI accessible to internal and external users, integrating AI models into existing applications, APIs, and systems.
• Collaborate with infrastructure and Dev Ops teams to deploy secure and scalable cloud and on-premise environments (including GPU partitioning), optimizing performance, resources, and costs.
• Partner with AI Engineers and cross-functional teams to transform prototypes into robust, production-grade AI solutions.
• Monitor and optimize the performance of AI applications, implementing observability best practices (logging, metrics, alerting) to detect incidents, data drift, and model deviations in production environments.
• Stay up to date with the latest developments in AI frameworks, cloud technologies, and software engineering practices, applying relevant improvements to production systems.

• Bachelor’s degree in Computer Science, Engineering, or another STEM field.
• 4+ years of experience in AI, Data Science, or ML Engineering applied to real-world environments.
• Strong programming skills in Python and solid understanding of software engineering principles (testing, clean code, CI/CD).
• Experience developing and deploying AI or ML solutions in Azure (e.g., Azure Machine Learning or Azure AI Services).
• Proficiency with PyTorch, FastAPI, and data/ML libraries such as Pandas or Scikit-learn.
• Experience with MLOps tools such as MLflow, Airflow, or Dagster.
• Experience with LLM frameworks (Hugging Face, Lang Chain, Llama Index) and agent-based automation (CrewAI, Agno, MCP, etc.).
• Knowledge of cloud-native infrastructure (Docker, Kubernetes, GPU partitioning).
• Familiarity with observability and model monitoring tools (Evidently
  
  AI, Inspect
  
  AI, Deep Eval).
• Experience with vector databases (Milvus, Open Search).
• Familiarity with distributed data processing (Dask, Polars) and LLM optimization (LoRA, QLoRA).
• Hands‑on experience with CI/CD pipelines (Git Hub Actions) and Dev Ops practices.

We offer you an excellent opportunity to grow and develop your career in a leading multinational organization.