Semantic Data and AI Engineer

Enterprise Knowledge (EK) is hiring for a full-time Semantic Data and AI Engineer to join our growing Knowledge and Data Services Sector. In this role, you will be responsible for designing and deploying cutting-edge data discovery, integration, and governance solutions for a wide range of organizations around the world. The Semantic Data and AI Engineer will be part of a team working on innovative projects and developing orchestrated data solutions to integrate, enrich, and transform a range of knowledge assets (structured and unstructured) for Artificial Intelligence (AI) solutions. This individual will be able to quickly learn new technologies and apply them to business challenges at large corporations, organizations, and federal agencies. The right candidate will have a passion for working with diverse data types and applying new methods and approaches to data challenges with a strategic mindset to advise clients on enterprise AI transformations. As an EK Semantic Data and AI Engineer , you will join a fast-growing company that is committed to equity and inclusion, have the opportunity to work in a collaborative workplace, take advantage of our unique benefits , and help build our innovative culture. To read more about the impactful work we are doing and to see the latest thought leadership from EK, follow us on LinkedIn . Responsibilities Work with data subject matter experts and business users to effectively understand and model their domain of knowledge Apply NLP techniques (entity extraction, classification, and document processing) to transform raw data and content into AI-ready assets Design, implement, test, and operate end-to-end RAG workflows for client engagements, including retrieval pipeline architecture, embedding strategies, and response evaluation Contribute to agentic AI solution design and implementation, including orchestration patterns, tool use, and memory and retrieval integration Support a variety of business intelligence projects using AI-based solutions Analyze complex datasets and communicate insights to both technical and non-technical stakeholders Design and implement data pipelines for ingesting, processing, and enriching structured and unstructured content using SQL, Python, R, or equivalent languages Contribute to semantic layer and knowledge graph implementations as part of larger AI solution architectures Work with internal and external teams to contextualize data engineering work into larger project context