Semantic AI Engineer

At Graphwise, we help enterprises transform fragmented data into connected, intelligent systems using Knowledge Graphs, semantic technologies, and modern AI architectures.

About the role

We’re looking for a strong Software Engineer with experience in data engineering and an interest in AI systems, data modeling, and large-scale information architectures. You don’t need to be a semantic technologies expert already - what matters most is solid engineering thinking, curiosity, and the ability to work with complex data problems.

Main Responsibilities:

• Design and build robust data pipelines for structured and unstructured data
• Integrate and harmonize data from multiple enterprise systems
• Work on AI-oriented retrieval and context architectures, including RAG and GraphRAG patterns
• Build workflows for extracting structured information from documents and text
• Contribute to scalable backend and data processing systems
• Collaborate with technical and business stakeholders to solve complex information challenges
• Explore and adopt modern AI, NLP, and data engineering technologies
  
  

Must-haves:

• Strong software engineering fundamentals
• Professional experience with Python, Java, or Scala
• Experience building backend systems or data pipelines
• Solid understanding of data modeling and ETL processes
• Familiarity with modern AI concepts such as: LLMs, RAG, vector databases, embeddings, or NLP workflows
• Experience with Git, CI/CD, and collaborative engineering practices
• Strong analytical and problem-solving skills
• Good communication skills in English
• Curiosity and willingness to learn new domains and technologies
  
  

Nice-to-haves:

• Knowledge Graphs or graph databases
• Semantic technologies such as RDF, OWL, SHACL, or SPARQL
• Ontology or taxonomy modeling
• NLP Basics: Basic understanding of Knowledge Extraction, specifically identifying and linking entities within text.
• NLP tooling such as SpaCy or similar libraries
• GraphRAG implementations
• Cloud platforms and distributed systems