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Key Responsibilities

7+ Years Elasticserach,RAG,Agentic AI,LLM

- Design, build, and optimize Elasticsearch indices, mappings, and analyzers for enterprise search use cases (GenAI search, semantic search, case deflection)
- Develop and tune hybrid search pipelines (keyword + vector/kNN search) using Elasticsearch's dense/sparse vector capabilities
- Build Retrieval-Augmented Generation (RAG) pipelines integrating Elasticsearch as the retrieval layer for LLM-based applications
- Design and implement agentic workflows multi-step reasoning, tool-calling, and orchestration using frameworks such as LangGraph, LangChain, or equivalent agent orchestration tools
- Integrate conversational AI/chatbot systems with Elasticsearch-backed knowledge bases and Salesforce Service Cloud or similar CRM platforms
- Implement query relevance tuning, ranking evaluation, and A/B testing for search quality improvements
- Develop and maintain ingestion pipelines (Logstash, Beats, or custom ETL) for structured/unstructured data into Elasticsearch
- Collaborate with Java/Spring Boot backend teams to expose search and agentic capabilities via APIs
- Support performance troubleshooting, cluster sizing, and scaling decisions across environments (dev/pre-prod/prod)
- Participate in sprint planning, estimation, and technical design reviews within Agile delivery teams

Required Skills

- Solid hands-on experience with Elasticsearch (indexing,



querying, mapping design, aggregations, relevance tuning)
- Experience with vector/semantic search (dense vector fields, kNN, ELSER, or similar)
- Working knowledge of Agentic AI concepts: multi-agent orchestration, tool/function calling, agent memory, and reasoning loops
- Practical experience with at least one agent framework (LangGraph, LangChain, AutoGen, CrewAI, or equivalent)
- Familiarity with RAG architecture patterns and prompt engineering for retrieval-grounded responses
- Proficiency in Java and Spring Boot for backend service integration
- Experience with REST APIs and integration with third-party platforms (e.g., Salesforce Service Cloud)
- Understanding of LLM providers/APIs (OpenAI, Anthropic, Azure OpenAI, or similar)
- Familiarity with CI/CD, Git, and Agile/Scrum delivery practices

Preferred/Nice-to-Have Skills

- Experience with Elastic's own AI/ML features (ELSER, inference endpoints, Elastic Learned Sparse Encoder)
- Experience with chatbot testing, conversational UX design, or multilingual NLP handling
- Knowledge of enterprise case management/deflection workflows
- Experience working in client-facing or consulting delivery model.

Warm regards, Laya Guptha| Senior IT Recruiter

- Email: [email protected]
- LinkedIn: https://www.linkedin.com/in/laya-guptha-jan10012000

📌 Software Developer (Hyderabad)
🏢 Tranzeal
📍 Hyderabad