Key Responsibilities Key Responsibilities:

• Design and Ontology Engineering: Design and evolve the formal ontology and semantic models (e.g., RDF, OWL) for our knowledge graph, accurately capturing complex domain knowledge and relationships.
• Graph Development & Implementation: Design, build, and optimize the knowledge graph architecture using graph database technologies (e.g., Neo4j, JanusGraph, Amazon Neptune).
• Querying and Analytics: Write complex, high-performance graph queries (e.g., Cypher, SPARQL)
• Collaboration: Work closely with Data Scientists, ML Engineers, Product Managers, and domain experts to translate business requirements into technical knowledge graph solutions that power search, recommendations, and AI/ML applications.
• Performance Tuning: Monitor, analyze, and optimize the performance of the graph database and associated pipelines for scalability and real-time query speed.

Essential Requirements

• Minimum of 3+ years of hands-on experience in designing and implementing large-scale Knowledge Graphs in a production environment.
• Deep expertise in ontology engineering, semantic modeling, and experience with standards like RDF, RDFS, OWL, and SPARQL.
• Proficiency with at least one major graph database (e.g., Neo4j, TigerGraph, AWS Neptune).
• Practical experience integrating LLMs with Knowledge Graphs (e.g., RAG, KG-powered AI agents).
• Strong programming skills in languages essential for data engineering, primarily Python.
• Experience applying NLP techniques for text processing and structuring (NER, relation extraction).
• Excellent problem-solving skills and the ability to work collaboratively in a fast-paced, agile environment.
• Excellent communication skills and ability to articulate complex AI concepts to diverse audiences.

Desired Skills (A Plus)

• Master's or Ph.D. in Computer Science, Artificial Intelligence, or a related technical field.
• Contributions to research (publications in top-tier conferences) or open-source projects.
• Experience with Google Cloud Platform and Vertex AI
• Knowledge of Natural Language Processing (NLP) techniques for information and entity extraction to populate the knowledge graph.
• Familiarity with Graph Machine Learning (e.g., GNNs - Graph Neural Networks).

Why Join Us?

• Work alongside top talent, united by a shared purpose and committed to making a real impact.
• Comprehensive private health coverage to ensure your physical and mental well-being.
• Company-sponsored gym membership to support your fitness goals.
• Hybrid work model offering flexibility to balance your professional and personal life.
• Coffee, tea, beverages, and snacks to keep you fueled throughout the day.
• Company events to celebrate achievements and enjoy time together.
• Get equipped with a MacBook to enhance your productivity and work experience.