Synergeticon GmbH

Software Engineer

• Development & Enhancement of the RAG Platform
• Design and implementation of Retrieval-Augmented Generation (RAG) architectures
• Development of document ingestion pipelines (PDF parsing, chunking, metadata processing)
• Implementation of embedding and vector search mechanisms
• Optimization of prompt strategies and LLM workflows
• Development of agentic workflows using LangGraph
• Design and integration of AI-powered coding agents
• Implementation of tool usage mechanisms and function calling
• Automation of code generation processes
• Design and implementation of knowledge graph structures (Neo4j)
• Entity and relationship extraction from documents
• Implementation of hybrid search architectures (vector search + graph traversal)
• Integration of LLM providers (OpenAI, Anthropic, AWS Bedrock, Ollama)
• Use of AWS services (S3, Lambda, Bedrock)
• Containerization using Docker
• Infrastructure automation with Terraform
• Implementation of integration tests for AI systems
• Evaluation of RAG systems (relevance, faithfulness)
• Data model validation using Pydantic
• Development of REST APIs with FastAPI

AI/ML Developer, RAG, AI Agents

AI Engineer

• Develop robust perception and AI systems for industrial and robotic applications
• Operate at the intersection of research and engineering
• Train models independently
• Translate cutting-edge research into prototypes
• Integrate prototypes into production-ready systems
• Apply and further develop classical and deep learning–based computer vision methods
• Independently implement, train, and debug models using PyTorch
• Optionally contribute NLP expertise in addition to computer vision
• Work with real industrial camera systems (if applicable)
• Use Docker for development and deployment workflows