Java developer with expertise in Spring/Kafka/Apache Camel

Job Summary :We are seeking a highly skilled and motivated Java Spring Boot Developer to join our engineering team. This role focuses on developing and deploying scalable, event-driven applications on OpenShift, with data ingestion from Apache Kafka and transformation logic written in Apache Camel. The ideal candidate should possess a strong understanding of enterprise integration patterns, stream processing, and protocols, and have experience with observability tools and concepts in AI-enhanced applications.

Key Responsibility :Design, develop, and deploy Java Spring Boot applications on Red Hat OpenShift.Build robust data pipelines with Apache Kafka for high-throughput ingestion and real-time processing.Implement transformation and routing logic using Apache Camel and Enterprise Integration Patterns (EIPs).Develop components that interface with various protocols including HTTP, JMS, and database systems (SQL/NoSQL).Utilize Apache Flink or similar tools for complex event and stream processing where necessary.Integrate observability solutions (e.g., Prometheus, Grafana, ELK, OpenTelemetry) to ensure monitoring, logging, and alerting.Collaborate with AI/ML teams to integrate or enable AI-driven capabilities within applications.Write unit and integration tests, participate in code reviews, and support CI/CD practices.Troubleshoot and optimize application performance and data flows in production environments

Required Skills & Qualification5+ years of hands-on experience in Java development with strong proficiency in Spring Boot.Solid experience with Apache Kafka (consumer/producer patterns, schema registry, Kafka Streams is a plus).Proficient in Apache Camel and understanding of EIPs (routing, transformation, aggregation, etc.).Strong grasp of various protocols (HTTP, JMS, TCP) and messaging paradigms.In-depth understanding of database concepts  both relational and NoSQL.Experience with stream processing technologies such as Apache Flink, Kafka Streams, or Spark Streaming.Familiarity with OpenShift or similar container platforms (Kubernetes, Docker).Knowledge of observability tools and techniques logging, metrics, tracing.Exposure to AI concepts (basic understanding of ML model integration, AI-driven decisions, etc.).