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Saiteja Vadla

@saitejavadla

I build enterprise GenAI assistants, RAG systems, and scalable data pipelines that improve knowledge access.

At FUJIFILM Dimatix, I build enterprise Generative AI solutions using Python, AWS Bedrock, Azure OpenAI, LangChain, LangGraph, RAG, and vector databases. I designed a knowledge assistant for 100,000+ engineering documents that reduced information retrieval time by 40%.

I also build data ingestion, ETL/ELT, hybrid retrieval, Graph RAG, and multi-agent workflows. Previously at Avis Hospital, I developed a patient support assistant and semantic search systems that reduced routine query handling by 40%.

Experience

Work history, roles, and key accomplishments

Current

GenAI Engineer

Current

Fujifilm Dimatix

Jan 2024 - Present (2 years 8 months)

Develop and deploy enterprise Generative AI solutions using Python, Azure OpenAI, AWS Bedrock, LangChain, and RAG. Designed an enterprise knowledge assistant reducing information retrieval time by 40% and improved retrieval precision by 25%.

Python Azure OpenAI OpenAI API Lang Chain RAG Embeddings Vector Databases PySpark AWS Glue S3 Lambda LangGraph Agentic AI Neo4j Graph RAG fastAPI Docker Kubernetes Langsmith Galileo LLM Evaluation AI Observability

AI/ML Engineer - NLP and Conversational AI

Avis Hospital

May 2021 - Dec 2022 (1 year 7 months)

Developed an AI-powered patient support assistant reducing routine query-handling effort by 40%. Built NLP-based semantic search and knowledge retrieval workflows across healthcare documents.

Python SQL NLP Semantic Search fastAPI Docker Summarization