AI Solutions Engineer | LLM Integration, RAG Systems & Autonomous Agents
Aktualisiert am 08.04.2026
Profil
Freiberufler / Selbstständiger
Remote-Arbeit
Verfügbar ab: 08.04.2026
Verfügbar zu: 50%
davon vor Ort: 50%
LLM Integration / Prompt Engineering
RAG (Retrieval-Augmented Generation)
AI Agent Development
Russian
Native
English
Professional working proficiency
German
Intermediate (B1)

Einsatzorte

Einsatzorte

Leipzig (+50km)
Deutschland, Schweiz, Österreich
möglich

Projekte

Projekte

2024 ? Present: Design and implement RAG-based systems


Role: AI Solutions Engineer | Self-employed


Tasks:

  • Design and implement RAG-based systems for automated data retrieval, analysis, and decision support
  • Build autonomous AI agents capable of multi-step task execution with tool integration
  • Develop LLM-powered automation pipelines for business process optimization
  • Integrate Claude and GPT models into production applications via API
  • Architect MCP (Model Context Protocol) server implementations for extended AI capabilities
  • Deploy and maintain AI-driven web applications on cloud infrastructure


Key projects:

  • AI-powered analytics platform with RAG pipeline for real-time data processing and insights generation
  • Multi-agent system for automated web auditing and compliance checking
  • Autonomous content generation and SEO optimization engine
  • Custom AI agent framework with tool use and memory management

2019 ? 2024: Built and scaled multiple e-commerce projects


Role: E-Commerce Manager | Self-employed


Tasks:

  • Built and scaled multiple e-commerce projects with focus on the German market
  • Managed end-to-end product lifecycle: sourcing, listing, marketing, fulfillment
  • Implemented data-driven decision making for inventory and pricing optimization
  • Developed automated workflows for order processing and customer communication

Aus- und Weiterbildung

Aus- und Weiterbildung

  • Continuous professional development in AI/ML through hands-on projects and research
  • Active contributor to open-source AI tooling and agent frameworks

Kompetenzen

Kompetenzen

Top-Skills

LLM Integration / Prompt Engineering RAG (Retrieval-Augmented Generation) AI Agent Development

Produkte / Standards / Erfahrungen / Methoden

Professional Summary

AI Solutions Engineer with 2 years of hands-on experience building LLM-powered applications, RAG pipelines, and autonomous AI agents. Background in e-commerce provides strong product thinking and business-oriented approach to AI solutions. Focused on turning complex AI capabilities into practical, production-ready systems.


Core Competencies

  • LLM Integration: Claude API, Anthropic SDK, OpenAI API, Prompt Engineering, Fine-tuning
  • RAG Systems: Vector Databases, Embeddings, Document Processing, Semantic Search, Chunking Strategies
  • AI Agents: Autonomous Agents, Multi-Agent Systems, Tool Use, Claude Agent SDK, MCP (Model Context Protocol)
  • Development: Python, TypeScript, Node.js, REST APIs, Docker
  • Infrastructure: Linux, VPS, Cloudflare, GCP, CI/CD

Einsatzorte

Einsatzorte

Leipzig (+50km)
Deutschland, Schweiz, Österreich
möglich

Projekte

Projekte

2024 ? Present: Design and implement RAG-based systems


Role: AI Solutions Engineer | Self-employed


Tasks:

  • Design and implement RAG-based systems for automated data retrieval, analysis, and decision support
  • Build autonomous AI agents capable of multi-step task execution with tool integration
  • Develop LLM-powered automation pipelines for business process optimization
  • Integrate Claude and GPT models into production applications via API
  • Architect MCP (Model Context Protocol) server implementations for extended AI capabilities
  • Deploy and maintain AI-driven web applications on cloud infrastructure


Key projects:

  • AI-powered analytics platform with RAG pipeline for real-time data processing and insights generation
  • Multi-agent system for automated web auditing and compliance checking
  • Autonomous content generation and SEO optimization engine
  • Custom AI agent framework with tool use and memory management

2019 ? 2024: Built and scaled multiple e-commerce projects


Role: E-Commerce Manager | Self-employed


Tasks:

  • Built and scaled multiple e-commerce projects with focus on the German market
  • Managed end-to-end product lifecycle: sourcing, listing, marketing, fulfillment
  • Implemented data-driven decision making for inventory and pricing optimization
  • Developed automated workflows for order processing and customer communication

Aus- und Weiterbildung

Aus- und Weiterbildung

  • Continuous professional development in AI/ML through hands-on projects and research
  • Active contributor to open-source AI tooling and agent frameworks

Kompetenzen

Kompetenzen

Top-Skills

LLM Integration / Prompt Engineering RAG (Retrieval-Augmented Generation) AI Agent Development

Produkte / Standards / Erfahrungen / Methoden

Professional Summary

AI Solutions Engineer with 2 years of hands-on experience building LLM-powered applications, RAG pipelines, and autonomous AI agents. Background in e-commerce provides strong product thinking and business-oriented approach to AI solutions. Focused on turning complex AI capabilities into practical, production-ready systems.


Core Competencies

  • LLM Integration: Claude API, Anthropic SDK, OpenAI API, Prompt Engineering, Fine-tuning
  • RAG Systems: Vector Databases, Embeddings, Document Processing, Semantic Search, Chunking Strategies
  • AI Agents: Autonomous Agents, Multi-Agent Systems, Tool Use, Claude Agent SDK, MCP (Model Context Protocol)
  • Development: Python, TypeScript, Node.js, REST APIs, Docker
  • Infrastructure: Linux, VPS, Cloudflare, GCP, CI/CD

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