• Design, develop, and maintain core components of a high-performance application built around knowledge graph architecture.

• Implement and optimize scalable backend solutions integrating with Graph database.

• Develop and support APIs (both REST and GraphQL) to expose and manage application functionality efficiently.

• Collaborate with cross-functional teams to ensure seamless data flow and performance through intelligent caching strategies.

• Analyze, debug, and enhance existing components using modern Java practices, ensuring maintainability and reliability.

What you’ll bring to the role:

• 12–18 years of hands-on experience in Java development with strong expertise in Core Java, Multithreading, and Object-Oriented Design.

• Proficiency with Spring Framework, Spring Boot, and deep understanding of Spring Annotations and Java-based configurations.

• Experience with Java 15 or later (Java 17 preferred).

• Strong experience in designing and developing RESTful APIs; good working knowledge of GraphQL.

• Deep understanding of distributed caching mechanisms, including Hazelcast, Caffeine, InCache, or Google Guava Cache.

• Experience integrating with Graph Databases (preferably Stardog); additional knowledge of Apache Jena and SAPRQL is a strong plus.

• Understanding of application security, authentication, and authorization best practices.

• Experience with ZooKeeper for coordination and distributed systems management.

• Strong understanding of system design principles, including scalability, fault tolerance, distributed systems, and performance optimization.

• At least 6 years' relevant experience would generally be expected to find the skills required for this role.

Good to Have:

• Experience or familiarity with Reactive Programming, especially using Spring WebFlux.

• Hands-on knowledge of HTTP clients like OkHttp, WebClient, or similar.

• Experience with or exposure to other graph databases or triple stores (e.g., Neo4j, Virtuoso, Blazegraph, RDF4J).

• Working knowledge of Redis for caching or data storage.

• Understanding of search and indexing systems similar to ElasticSearch used for building scalable and efficient search features.

• Experience with analytical or relational databases, particularly in the context of data access and API integration.

• Exposure to observability and monitoring tools such as Prometheus, Grafana, Loki, Kibana or Splunk.