div:has([data-free-thinking-preview-answer=true])+:is(.text-message,.relative:has(>.text-message))]:-mt-2 grow">

Job Summary:
The Java/RAG Developer will design, develop, and deploy AI-powered applications using Java, Spring Boot, and Retrieval-Augmented Generation (RAG) technologies. The role will focus on building production-grade RAG pipelines, scalable microservices, event-driven architectures, and cloud-native solutions on AWS. The engineer will collaborate with data, platform, and product teams to define technical direction, deliver scalable solutions, and contribute to engineering standards and mentorship.

Key Responsibilities:
• Architect and develop RAG-based features that integrate LLM capabilities into existing product workflows.
• Design and implement end-to-end RAG pipelines, including document ingestion, chunking, embedding, vector storage, retrieval, and generation.
• Develop high-throughput Java microservices backed by Kafka event streams.
• Design, develop, and maintain RESTful APIs and distributed microservices.
• Design and operate event-driven architectures using Kafka and related technologies.
• Package, deploy, and operate containerized services on Amazon EKS using Helm.
• Write and maintain Helm charts for Kubernetes deployments.
• Manage AWS infrastructure components, including EC2 instances, networking, and IAM.
• Implement and support vector database solutions such as Pinecone, Weaviate, pgvector, or OpenSearch.
• Integrate and maintain LLM orchestration frameworks such as LangChain, LlamaIndex, or similar technologies.
• Work with NoSQL databases such as MongoDB or Amazon DocumentDB and caching technologies such as Redis.
• Collaborate with data, platform, and product teams to define technical direction and architecture.
• Support CI/CD processes using tools such as Harness and monitor application health using platforms such as Splunk.
• Mentor junior engineers and contribute to engineering standards, development practices, and continuous improvement.

Required Qualifications:
• Strong proficiency in core Java and Spring Boot/Spring Cloud.
• Hands-on experience designing and implementing RAG pipelines, including document ingestion, chunking, embedding, vector storage, retrieval, and generation.
• Experience with vector databases such as Pinecone, Weaviate, pgvector, or OpenSearch.
• Experience with LLM orchestration frameworks such as LangChain, LlamaIndex, or similar technologies.
• Strong experience building RESTful APIs and scalable microservices.
• Experience designing and operating event-driven architectures.
• Experience deploying and managing containerized workloads on Amazon EKS.
• Experience writing and maintaining Helm charts for Kubernetes deployments.
• Working knowledge of AWS EC2, networking, and IAM.
• Experience with NoSQL databases such as MongoDB or Amazon DocumentDB.
• Experience with caching solutions such as Redis.
• Strong communication and collaboration skills.
• Experience working in Agile development environments.
• Bachelor's or master's degree in Computer Science, Engineering, or equivalent experience.
• Self-driven approach with strong ownership and ability to take initiative.

Preferred Qualifications:
• Experience with Kafka Connect or Kafka Streams.
• Experience with CI/CD tools such as Harness.
• Experience with monitoring and logging platforms such as Splunk.
• Experience mentoring junior engineers and contributing to engineering standards.