Senior Java Developer (Kafka and AI)

Job Description:

• Design, build, and maintain scalable microservices in Java (17+) and Spring Boot that produce and consume events through Apache Kafka.
• Own Kafka topic design, partitioning strategy, consumer group tuning, schema management, and delivery guarantees (at-least-once and exactly-once semantics).
• Build real-time stream processing with Kafka Streams, ksqlDB, or Apache Flink, and integrate systems with Kafka Connect.
• Integrate AI capabilities into applications, including LLM APIs, retrieval-augmented generation (RAG), embeddings, and vector search, using frameworks such as Spring AI or LangChain4j.
• Build streaming data pipelines that feed AI and ML models with clean, timely data, and deploy model-serving endpoints alongside existing services.
• Ensure performance, security, and observability across services through monitoring, logging, tracing, and automated testing.
• Participate in code reviews, architecture discussions, and Agile ceremonies, and mentor junior developers.

Required Qualifications

• 8+ years of professional software development experience with Java, including Java 11 or later.
• 8+ years of hands-on experience with Apache Kafka in production, including producers, consumers, topic design, and performance tuning.
• Experience building microservices and REST APIs with Spring Boot.
• Experience with Kafka Streams, Kafka Connect, and Schema Registry (Avro or Protobuf).
• Hands-on experience integrating AI or ML into applications, such as calling LLM APIs, building RAG workflows, or deploying ML models behind services.
• Experience with relational and NoSQL databases (for example PostgreSQL, Oracle, MongoDB, or Cassandra).
• Experience with containers and orchestration (Docker, Kubernetes) and CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI, or similar).
• Experience with at least one major cloud platform: AWS, Azure, or Google Cloud Platform.
• Bachelor's degree in Computer Science or a related field, or equivalent professional experience.

Preferred Qualifications

• Experience with Spring AI, LangChain4j, or similar Java AI frameworks.
• Experience with vector databases (pgvector, Pinecone, Weaviate, Milvus, or Elasticsearch vector search).
• Experience with managed Kafka services such as Confluent Cloud, Amazon MSK, or Azure Event Hubs.
• Experience with Apache Flink or Spark Structured Streaming.
• Familiarity with Python for working alongside data science teams.
• Experience with observability tools such as Prometheus, Grafana, Splunk, or Datadog.
• Confluent Certified Developer for Apache Kafka, or a cloud certification (AWS, Azure, Google Cloud Platform).
• Experience in public sector, financial services, or other regulated environments.