Freelancer profile translated to English.

Description

I am a Python developer with several years of experience in backend development and a growing specialization in Artificial Intelligence, particularly in the areas of Natural Language Processing (NLP) and Large Language Models (LLMs).

My professional background combines technology and language: in recent years, I have developed scalable backend systems (Python, FastAPI, Flask, REST APIs, AWS) while deepening my passion for language, communication, and semantic AI projects.

Currently, I am expanding my knowledge in Agentic AI, LangChain, and LLM integration – with the goal of developing AI systems that can understand and meaningfully utilize language.

I work in a structured, reliable manner and place great importance on quality, readability, and clarity in code. My linguistic precision also allows me to convey complex technical topics understandably – whether in documentation, concepts, or during knowledge exchange within a team.

💡 Focus Areas:

Python Backend Development

Natural Language Processing (NLP)

Large Language Models (LLMs), LangChain

API Development & Data Processing

Cloud (AWS, GCP)

Technical Documentation & Clear Communication

📍 Location: Leonberg (Stuttgart region) | Remote or Hybrid

Languages

German
Native or bilingual
English
Fluent
French
Fluent
Spanish
Fluent

Workplace preferences

Can work on-site

Stuttgart (up to 50km)

LILT AI
AI Benchmark Engineer
May 2026 - July 2026 (2 months)
Task Engineering: Evaluation of coding agents.
Asset Creation: Development of realistic test environments using datasets and files in German. It is crucial that these assets remain in the target language to truly measure multilingual processing.
Prompting & Translation: Identification of weaknesses where AI systems fail in German.
Implementation & Verification: Support in developing robust solutions (reference implementations) and creating highly reliable, deterministic verifier scripts (rubric-based evaluation only if absolutely necessary).
Calibration & Execution: Analysis of execution logs and calibration of task difficulty (Easy to Very Hard) using standard terminal benchmark configurations across different model tiers (Haiku, Opus).
Quality Assurance: Participation in a rigorous, four-stage human quality control process (creation, human review, calibration check, and audit) as well as automated LLM-based checks to ensure fairness, grammatical correctness, and benchmark integrity.
Linguistic Review: Review of AI benchmark tasks in Hindi, Arabic, Japanese, Chinese, Czech, and Turkish.
AI Benchmarking Coding Agents Agentic AI Large Language Models
Digitale Leute School
AI Software Engineer
January 2026 - April 2026 (3 months)
Stuttgart, Germany
Further training in AI Software Engineering at Digitale Leute
• Fundamentals of modern software architectures for AI systems
• Engineering Principles, Best Practices & Clean Code
• Cloud-based Development & Deployment
• Testing, Monitoring & Quality Assurance of AI Systems
• Responsible AI, Security, Privacy & Compliance
• Development of AI-powered Applications (MVP → Production)
• Prompt Engineering & LLM-based Features
• Advanced Prompting & Evaluation
• Deployment & Monitoring of AI Applications
• Refactoring & Robustness of AI Code
• Development of Agentic AI Systems
• Orchestration of Complex AI Workflows
• Tool Integration & Automation
• Multi-Agent Systems & AI Workflows
• Architecture & Scaling of Agentic Systems
• Agile Methodologies & Collaboration in Cross-functional Teams
• Roadmapping, Planning & Iterative Development
• Analysis of User Behavior & Application Monitoring
• KPIs, Tracking Events & Evaluation of AI Features
• Manual Testing & Bug Reporting
Tools & Technologies
Python · LLMs · Prompt Engineering · Cloud Platforms · Docker · Git ·
CI/CD · Monitoring Tools · AI Frameworks · API Design · Agile
Workflows
Python Large Language Models (LLMs) CI/CD MVP AI Agents
insightfabrix
Backend Software Developer
November 2024 - November 2025 (1 year)
Schorndorf, Germany
Development of an app for automatic installation of databases, relations, and functions using Python and Django. Includes a main Django model and three inline models for apps, users, and Git repositories with SQL files. Databases are created for clients in the die-casting industry. Prototyping with Large Language Models and LangChain for chat-based customer support.
Python/Django SQL PostgreSQL Python Backend Large Language Models