Semantic AI Engineer

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    "description": "<p><span style=\"font-size: 12pt\">At Graphwise, we help enterprises transform fragmented data into connected, intelligent systems using Knowledge Graphs, semantic technologies, and modern AI architectures.<br><br></span></p>\n<p><span style=\"font-size: 14pt; font-weight: bold\">About the role</span></p>\n<p><span style=\"font-size: 12pt\">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.<br><br></span></p>\n<p><span style=\"font-size: 14pt; font-weight: bold\">Main Responsibilities:<br><br></span></p>\n<ul>\n<li><span style=\"font-size: 12pt\">Design and build robust data pipelines for structured and unstructured data</span></li>\n<li><span style=\"font-size: 12pt\">Integrate and harmonize data from multiple enterprise systems</span></li>\n<li><span style=\"font-size: 12pt\">Work on AI-oriented retrieval and context architectures, including RAG and GraphRAG patterns</span></li>\n<li><span style=\"font-size: 12pt\">Build workflows for extracting structured information from documents and text</span></li>\n<li><span style=\"font-size: 12pt\">Contribute to scalable backend and data processing systems</span></li>\n<li><span style=\"font-size: 12pt\">Collaborate with technical and business stakeholders to solve complex information challenges</span></li>\n<li><span style=\"font-size: 12pt\">Explore and adopt modern AI, NLP, and data engineering technologies<br><br></span></li>\n</ul>\n<p><span style=\"font-size: 14pt; font-weight: bold\">Must-haves:<br><br></span></p>\n<ul>\n<li><span style=\"font-size: 12pt\">Strong software engineering fundamentals</span></li>\n<li><span style=\"font-size: 12pt\">Professional experience with Python, Java, or Scala</span></li>\n<li><span style=\"font-size: 12pt\">Experience building backend systems or data pipelines</span></li>\n<li><span style=\"font-size: 12pt\">Solid understanding of data modeling and ETL processes</span></li>\n<li><span style=\"font-size: 12pt\">Familiarity with modern AI concepts such as: LLMs, RAG, vector databases, embeddings, or NLP workflows</span></li>\n<li><span style=\"font-size: 12pt\">Experience with Git, CI/CD, and collaborative engineering practices</span></li>\n<li><span style=\"font-size: 12pt\">Strong analytical and problem-solving skills</span></li>\n<li><span style=\"font-size: 12pt\">Good communication skills in English</span></li>\n<li><span style=\"font-size: 12pt\">Curiosity and willingness to learn new domains and technologies<br><br></span></li>\n</ul>\n<p><span style=\"font-size: 14pt; font-weight: bold\">Nice-to-haves:</span></p>\n<ul>\n<li><span style=\"font-size: 12pt\">Knowledge Graphs or graph databases</span></li>\n<li><span style=\"font-size: 12pt\">Semantic technologies such as RDF, OWL, SHACL, or SPARQL</span></li>\n<li><span style=\"font-size: 12pt\">Ontology or taxonomy modeling</span></li>\n<li><span style=\"font-size: 12pt\">NLP Basics: Basic understanding of Knowledge Extraction, specifically identifying and linking entities within text.</span></li>\n<li><span style=\"font-size: 12pt\">NLP tooling such as SpaCy or similar libraries</span></li>\n<li><span style=\"font-size: 12pt\">GraphRAG implementations</span></li>\n<li><span style=\"font-size: 12pt\">Cloud platforms and distributed systems</span></li>\n</ul>",
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