We are a technology-driven organization building innovative AI-powered platforms that solve complex real-world challenges at scale. By combining data, intelligence, and modern cloud technologies, we create solutions that enhance user experiences, drive impactful outcomes, and enable organizations to make smarter decisions.

We foster a culture of innovation, ownership, collaboration, and continuous learning, empowering our teams to build transformative products and scalable technology platforms.

Design and own the enterprise knowledge graph platform, including architecture, infrastructure, data models, and ontology standards.

Build and maintain knowledge graphs representing complex domains, taxonomies, entities, relationships, and interconnected datasets.

Enable GraphRAG architectures by integrating knowledge graphs with Large Language Models (LLMs) and AI retrieval systems.

Define ontology governance frameworks, schema standards, versioning strategies, and quality assurance processes.

Optimize graph database performance through query tuning, indexing, partitioning, and scalability improvements.

Build entity resolution and knowledge extraction pipelines from structured and unstructured data sources.

Develop semantic search capabilities using graph-based and vector-based retrieval approaches.

Collaborate with AI and Machine Learning teams to develop graph-powered recommendations, intelligent insights, and reasoning capabilities.

Evaluate emerging graph technologies and evolve the platform architecture to support growing business needs.

Establish data quality standards, governance controls, validation frameworks, and remediation processes across the knowledge graph ecosystem.

Drive graph-based integration across diverse data sources and enable semantic AI applications through advanced reasoning frameworks.

Required Skills

Strong experience designing, implementing, and managing Graph Database solutions in production environments.

Deep expertise in Knowledge Graphs, Ontologies, Semantic Technologies, and Graph Data Modeling.

Hands-on experience with graph databases such as Neo4j, JanusGraph, Apache Jena, or similar platforms.

Strong knowledge of RDF, Property Graphs, SPARQL, and Cypher query languages.

Experience building and maintaining large-scale ontologies and enterprise knowledge graph platforms.

Understanding of ontology governance, schema evolution, versioning, and metadata management.

Experience with graph-based data integration, semantic reasoning, and knowledge representation techniques.

Familiarity with AI, LLMs, Retrieval Augmented Generation (RAG), and GraphRAG concepts.

Strong analytical, problem-solving, and architecture design skills.

Excellent communication and stakeholder management abilities.

Preferred Qualifications

Experience designing platforms that support AI, recommendation engines, semantic search, or intelligent retrieval systems.

Exposure to vector databases, embeddings, and hybrid search architectures.

Knowledge of data governance, metadata management, and enterprise-scale information architecture.

Opportunity to architect and build a strategic knowledge graph and semantic AI platform from the ground up.

Work on cutting-edge technologies spanning Graph Databases, Knowledge Graphs, GraphRAG, Semantic Search, and AI-powered applications.

High-impact role with ownership over architecture, technology decisions, and platform evolution.

Collaborative environment focused on innovation, experimentation, and technical excellence.

Opportunity to work alongside AI, data science, engineering, and product teams on next-generation intelligent systems.

Competitive compensation, comprehensive benefits, and strong career growth opportunities.

Chance to solve complex large-scale data challenges and shape the future of AI-powered knowledge systems