TI
Senior Elasticsearch Engineer – RAG & Agentic AI
Tranzeal Inc.
🇮🇳 India
On-site
Senior
2 weeks ago
- Elasticsearch
- RAG
- Machine Learning
- LangGraph
- LangChain
- AI
- Salesforce Service Cloud
- CRM
- Logstash
- ETL
- Java
- Spring Boot
- Agile
- AutoGen
- CrewAI
- REST API
- OpenAI
- Azure OpenAI
- CI/CD
- Git
- Scrum
- Elastic
- AI/ML
- Natural Language Processing
2 weeks ago
Experience: 7+
Salary: 28 LPA Max
Work Mode : Remote
Key Responsibilities
- 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
- Strong 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 models
Senior Elasticsearch Engineer – RAG & Agentic AI · Tranzeal Inc.