# DharaniTheja Kanjeri

> Generative AI Engineer | LLMs • RAG • LangChain • AI Copilots • AWS • Kubernetes | Production-Scale AI Systems

Location: Youngstown, Ohio, United States
Profile: https://flows.cv/dharanitheja

Generative AI Engineer with 5+ years of experience building production-grade AI systems across machine learning, data science, and enterprise Generative AI applications. I specialize in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and enterprise AI copilots that enable intelligent knowledge discovery at scale.
 
Currently, I design and deploy real-time GenAI solutions using LangChain, vector databases, and cloud-native infrastructure. My work focuses on building scalable RAG pipelines, optimizing prompt performance, and implementing LLMOps frameworks with monitoring, safety guardrails, and access-aware retrieval for secure enterprise deployments.
 
Previously, I developed end-to-end machine learning platforms, including customer churn prediction systems that improved retention and protected $1.8M+ in annual revenue. I bring strong expertise in Python, AWS, Kubernetes, and distributed data systems, with a focus on translating complex business problems into production-ready AI solutions.
 
I’m passionate about building reliable, scalable, and secure AI systems that deliver measurable business impact.
 
Core Expertise:
 • Generative AI & LLM Applications
 • Retrieval-Augmented Generation (RAG)
 • Enterprise AI Copilots
 • LLMOps / MLOps
 • Cloud-Native AI Deployment (AWS, Kubernetes)

## Work Experience
### Generative AI Engineer @ Glean
Jan 2025 – Present | United States
Built a production-grade enterprise AI copilot for unified workplace search using RAG architecture, serving 5K+ daily users and improving knowledge discovery efficiency. Architected an enterprise knowledge platform integrating fragmented tools using Python, LangChain, and LlamaIndex, processing 12M+ documents. Engineered high-performance RAG pipelines using Pinecone and FAISS with OpenAI GPT and LLaMA, enabling permission-aware semantic search. Optimized LLM performance using prompt engineering, context enrichment, and query rewriting, reducing hallucinations and improving response accuracy. Deployed real-time AI search services using FastAPI, Docker, and Kubernetes on AWS, achieving sub-120ms latency. Implemented enterprise LLMOps pipelines using LangSmith, MLflow, and Weights & Biases with Guardrails AI for compliance and security

### Data Scientist @ Tata Consultancy Services
Jan 2020 – Jan 2024 | India
Built an end-to-end churn prediction platform evolving from analytics to real-time ML system with MLOps and cloud deployment. Improved model ROC-AUC from 0.72 to 0.89 through feature engineering and model optimization. Developed scalable data pipelines integrating PostgreSQL, MySQL, and AWS S3 processing 10M+ records daily. Built machine learning models (Logistic Regression, Random Forest, XGBoost) improving prediction precision by 20%. Deployed real-time inference services using FastAPI, Flask, Docker, and Kubernetes with CI/CD pipelines. Designed executive dashboards in Power BI and Tableau reducing churn by 15% and protecting $1.8M revenue. Conducted exploratory data analysis to identify behavioral trends and enable targeted retention campaigns


## Education
### Master of Science in Data Science and Statistics
Youngstown State University


## Contact & Social
- LinkedIn: https://linkedin.com/in/dharanitheja-kanjeri-423101352

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Source: https://flows.cv/dharanitheja
JSON Resume: https://flows.cv/dharanitheja/resume.json
Last updated: 2026-04-16