// AI Engineer in Europe
AI engineer for European teams building agent workflows and automation.
For European teams, I bring AI engineering as the main skill and the software/devops/backend/Linux stack needed to make AI systems usable in real workflows.
Based in Germany, open to European roles, relocation and remote/hybrid AI engineering work.
Proof points
- Stuttgart-based with Germany experience through Porsche Digital and Hochschule Trier.
- Builds confidential/local LLM workflows and AI-assisted document analysis systems.
- Built a Porsche Digital internal LLM routing system around local inference and cloud-provider selection.
- Can work across AI, software engineering, DevOps, backend and Linux-heavy implementation surfaces.
Relevant work
- May 2026 to present
EFQM/RADAR AI Report Analyzer
A local-first, multi-agent RAG pipeline for the first-pass desk assessment of EFQM-based organizational self-assessment reports. It retrieves assessment guidance, links findings to source evidence, flags gaps and conflicts, and produces structured draft feedback for human review. I lead the five-person team and enforce fail-closed scoring, typed agent contracts, reproducible run provenance, and CI evaluation gates.
Read case study - 2025 — 2026
LLM Routing System
An internal on-device LLM routing layer that classifies each prompt by task type and complexity before selecting a local model or cloud provider. My operational estimate was that roughly 65 percent of requests stayed local, reducing cloud AI spend by about 45 percent. These are self-reported estimates rather than figures from a controlled finance study.
Read case study - 2025 to 2026
Vehicle Software Infrastructure
Built and maintained CI/CD pipelines for Dockerized C++ and Python backend services on embedded Linux across ARM and x86 targets. I taught myself Rust on the job and implemented a REST-based OTA update mechanism on three test vehicles with automated version checks, fallback logic, health monitoring, and service orchestration.
Read case study - 2025 to 2026
Edge AI Computer Vision Prototype
Real-time object detection prototype using GStreamer and YOLO on embedded ARM and x86 hardware. The modular pipeline separates preprocessing, inference, post-processing, and visualization, then produces visual overlays and structured detection metadata for downstream feedback experiments.
Read case study - Oct 2024 — Mar 2025
EUNO: ML-Based Mood Tracker (Graduation Project)
ML-based mood tracker with a Random Forest model that reached about 87 percent accuracy after feature engineering and SMOTE class balancing. A FastAPI backend runs the preprocessing and prediction path, while Flutter, SQLite, and Firebase support the application. Built with Jaser Quteshat under Dr. Ahmad Barghash.
Read case study
Search fit
- AI engineer Europe
- remote AI engineer Europe
- AI automation engineer Europe
- RAG engineer Europe