NLP/Semantic Engineer/Semantic Solution Engineer
PrivateAI is an AI-powered data governance and knowledge-graph platform focused on securely processing, analyzing, validating, and monetizing research and other data assets. It serves researchers, data analytics and GenAI companies, healthcare organizations, enterprises, and data contributors.
Maintainer signals as of 9/25/2026
Funding history
About PrivateAI
PrivateAI develops a privacy-focused AI platform that converts unstructured data into datasets and knowledge graphs for search, visualization, analysis, and discovery of hidden relationships. Its ecosystem includes a data marketplace, peer-to-peer research collaboration, crowdsourced data contribution, encrypted data handling, AI analytics, and PGPT token-based payments and rewards. The organization offers free, premium, and enterprise plans for individuals, research labs, commercial data and AI companies, healthcare organizations, and larger businesses.
Skills
About the Role
You will lead the strategy and development of enterprise semantic solutions, researching cutting-edge approaches and toolkits to solve complex problems in the semantic and ontology domain. You will design and implement semantic layer solutions such as taxonomy and ontology management tools, graph databases, triple stores, and labeled property graphs. You'll interpret existing semantic schemas, help develop solution architectures and governance plans, and ensure the quality, interoperability, and reusability of data and knowledge assets following FAIR Data Principles and Semantic Web standards.
Requirements
- At least 3 years designing and managing taxonomies, thesauri, and/or ontologies
- Expertise in knowledge engineering, knowledge representation, ontology development, and use of generative AI and LLMs in complex scientific domains
- Expertise in FAIR Data Principles and the Semantic Web technology stack (SHACL, RDF, RDF*, OWL, etc.) and experience using ontology development tools
- Strong belief in the business applications of knowledge graphs and ability to adapt to new technology
- Experience using semantic standards like RDF, OWL, SKOS, and SPARQL
- Programming experience such as Java, C/C++, or Python
- Experience or knowledge in data modeling, NLP, pattern recognition, and knowledge graphs
- Experience in natural language processing tools and platforms such as spaCy and computational linguistics
- Knowledge of cloud platforms such as AWS, Azure, or GCP and containerization with Docker or Kubernetes
- Experience with SQL and NoSQL databases
- Understanding of HTML, CSS, and JavaScript
- Bachelor's degree in Computer Science, Information Science, Knowledge Management, Library Science, Data Science, or a related field
Responsibilities
- Research state-of-the-art approaches and toolkits for solving problems related to the semantic and ontology domain
- Propose methodologies covering various text/image/graph/chart analysis challenges
- Lead the strategy, design and development of enterprise semantic solutions such as metadata, taxonomies, ontologies and knowledge graphs
- Lead the implementation of semantic layer solutions such as taxonomy/ontology management tools, graph databases/triple stores and labeled property graphs
- Interpret existing semantic schemas and help develop and deliver design and implementation of solutions architectures and governance plans
- Ensure the quality, interoperability and reusability of data and knowledge assets following FAIR Data Principles and Semantic Web standards
Benefits
- Market-competitive remuneration
- Performance-dependent bonuses including commission from funding raised
- Vesting in the form of tokens
- Access to personal networks and prestigious memberships of the company, its advisors, and the CEO
- Paid invitations to conferences or business events in global tech and finance hotspots