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We are seeking a highly skilled Lead Java Developer with expertise in OpenSearch and vector search to create advanced conversational search functionality using Retrieval-Augmented Generation (RAG) architecture.
Responsibilities
- Design and develop scalable applications utilizing Amazon OpenSearch and AWS to deliver conversational search solutions
- Update and enhance OpenSearch plugins to enable semantic search and vector search capabilities
- Integrate Large Language Models (LLMs) with RAG architecture to facilitate high-quality conversational AI solutions
- Lead the creation of a vectorized index ensuring efficient and accurate search queries
- Optimize application performance to maintain seamless interactions between search systems and technologies
- Collaborate with cross-functional teams to address architectural and technical challenges
- Analyze, troubleshoot, and resolve issues involving OpenSearch, Elasticsearch, or related systems
- Provide guidance and mentorship to junior developers on best practices in OpenSearch and Java development
- Align with project goals to support the delivery of enterprise-grade search solutions
Requirements
- 5+ years of professional experience with Java and related frameworks
- At least 1 year of relevant leadership background
- Proficiency in Amazon OpenSearch, Elasticsearch, and AWS-based solutions for search-driven applications
- Expertise in search engines, text analytics, and semantic web integration
- Background in integrating LLMs with RAG architecture for conversational search capabilities
- Familiarity with updating and customizing OpenSearch plugins to enhance search functionality
- Skills in GitHub for version control and Docker for containerized application deployment
- Capability to troubleshoot and resolve issues with search-related technologies
- Understanding of Java design patterns and scalable application design principles
- Excellent command of written and spoken English (B2+ level)
Nice to have
- Understanding of Apache Lucene Core to enhance search functionalities
- Showcase of deploying containerized applications efficiently with Docker
- Proficiency in collaborative development practices with GitHub
- Background in implementing Retrieval-Augmented Generation (RAG) solutions within search-focused environments
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