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.
