Experience
3+ years Core Skills
RDF, SPARQL, Python, Knowledge Graph Candidate’s location
Europe, Ukraine Work Model
Remote Engagement
Full-time, long-term English
Upper-Intermediate+
We are looking for an AI and Knowledge Graph Engineer to join our client’s team and contribute to building an AI-driven recruitment SaaS platform from scratch. You will work on production AI services, RDF-based Knowledge Graphs, semantic search, and intelligent data processing to help transform and automate the recruitment lifecycle.
About the project — our client is building an AI-driven, end-to-end recruitment SaaS platform from scratch, designed to transform and automate the entire recruitment lifecycle. The platform covers everything from capturing client requirements, validating and publishing job openings to evaluating candidates, managing recruiter-candidate communication, supporting interviews, negotiations, onboarding, and payroll processes.
At the core of the solution are advanced AI technologies, knowledge graphs, and ontologies that enable intelligent candidate matching based on skills, experience, and semantic relationships rather than traditional keyword-based searches. The project also incorporates AI-powered communication, interview analysis, and sentiment analysis to streamline recruitment workflows and support more informed hiring decisions.
As an AI and Knowledge Graph Engineer, you will design, develop, and maintain production AI services and RDF-based Knowledge Graphs. You will work on information extraction, entity resolution, semantic search, and graph-based data processing, contributing to technical decisions and ensuring AI-powered solutions are reliable, testable, and ready for real-world production environments.
Must have:
3+ years of experience in AI/ML Engineering, Knowledge Graph Engineering, or Semantic Data Engineering.Hands-on experience developing and deploying production AI services and RDF-based Knowledge Graphs.Strong Python development skills, including FastAPI, Pydantic, and SQL.Practical experience with RDF, SPARQL, ontology design, and semantic data modeling.Experience with SHACL validation, taxonomies, and knowledge graph standards.Hands-on experience with RDF graph databases such as GraphDB, Stardog, Apache Jena, Amazon Neptune, or similar.Experience with NLP, information extraction, and entity resolution techniques.Understanding of embeddings, semantic search, hybrid retrieval, and reranking approaches.Experience building reliable data ingestion and transformation pipelines.Strong understanding of automated testing, data validation, and production debugging.Experience with asynchronous processing, timeouts, retries, and error handling.Familiarity with model evaluation techniques, including precision, recall, and labeled datasets.Upper-Intermediate English level or higher.Strong analytical, problem-solving, and communication skills.
Good to have:
Experience with Microsoft Foundry, Azure ML, or MLflow.Familiarity with Azure AI Search or OpenSearch.Experience with PyTorch, sentence-transformers, spaCy, or scikit-learn.Knowledge of SKOS, PROV-O, JSON-LD, and OWL reasoning.Experience with Parquet, Delta Lake, or learning-to-rank approaches.Understanding of event-driven architectures and distributed systems.
Responsibilities:
Design, develop, and maintain production-ready Python services for information extraction, entity resolution, and semantic search.Build and evolve RDF-based Knowledge Graphs, including ontology design, semantic relationships, provenance, and temporal context.Develop and optimize SPARQL queries, graph ingestion pipelines, and RDF data validation processes.Implement reliable data mapping and ingestion workflows, supporting incremental updates, idempotent processing, and full rebuilds.Develop NLP pipelines to extract structured information from documents, forms, messages, and transcripts.Implement entity matching, normalization, similarity scoring, and resolution mechanisms.Build and improve lexical, vector, and hybrid search capabilities using embeddings, reranking, and graph queries.Evaluate AI models and extraction pipelines using labeled datasets, precision/recall metrics, and reproducible testing.Ensure reliability, performance, and maintainability through automated testing, monitoring, and fault diagnosis.Apply responsible AI practices, including data minimization, prompt-injection testing, human review, and fallback mechanisms.Collaborate with the engineering team on architecture, technical decisions, integrations, and continuous improvements.
We offer:
Competitive salary with regular reviews.Medical insurance after a 3-month probation period (available in Ukraine).Vacation (up to 20 working days).Paid sick leave (10 working days).11 national holidays as additional days off.Online English courses.Accountant assistance and legal support.Flexible working schedule with remote, office-based, or hybrid work options.Fully equipped office space located in the city center, ready for work during power outages.Direct cooperation with the customer.Dynamic environment with minimal bureaucracy and great team spirit.Challenging projects across diverse business domains and a variety of technology stacks.Opportunities to collaborate with top-level and senior specialists to strengthen your technical skills.Online and offline team-building activities.Support for volunteering initiatives and the development of a volunteering culture.
Ready to take the next step? Apply now and let’s talk about how you can make an impact on the project.
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