Job Description
Primary Responsibilities:
- Built and implemented enterprise-level Gen AI chatbots capable of natural-language search over extensive document repositories and databases.
- Research and develop multi-agentic systems for production-grade applications that handle large-scale documents and big data
- Optimize vector databases for enterprise-scale semantic search, context management, chat history, and source attribution
- Build document processing pipelines with intelligent chunking, metadata extraction, and multi-format handling
- Implement advanced retrieval strategies: hybrid search, re-ranking, and custom evaluation frameworks
- Work in AWS cloud platform for deployment – handle concurrent requests and scale
- Integrate and optimize LLMs via AWS Bedrock, or Azure with hallucination mitigation
- Debug and resolve retrieval quality issues, latency bottlenecks, and cost optimization challenges
- Opportunity to mentor and shape Gen AI practices across the organiza...
- Built and implemented enterprise-level Gen AI chatbots capable of natural-language search over extensive document repositories and databases.
- Research and develop multi-agentic systems for production-grade applications that handle large-scale documents and big data
- Optimize vector databases for enterprise-scale semantic search, context management, chat history, and source attribution
- Build document processing pipelines with intelligent chunking, metadata extraction, and multi-format handling
- Implement advanced retrieval strategies: hybrid search, re-ranking, and custom evaluation frameworks
- Work in AWS cloud platform for deployment – handle concurrent requests and scale
- Integrate and optimize LLMs via AWS Bedrock, or Azure with hallucination mitigation
- Debug and resolve retrieval quality issues, latency bottlenecks, and cost optimization challenges
- Opportunity to mentor and shape Gen AI practices across the organiza...
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