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Hello, I’m Narasimha Arepalli, a senior AI/ML & Generative AI Engineer with 10+ years delivering scalable, production-grade AI and data solutions across telecom, government, healthcare, and enterprise domains. I design, build, and deploy end-to-end AI/ML and Generative AI systems using cloud-native architectures across Azure, AWS, and GCP, with hands-on experience with LLMs such as GPT, LLaMA, BERT, and Claude. I’ve built conversational AI, document intelligence platforms, and retrieval-augmented generation (RAG) pipelines, and I frequently leverage LangChain, OpenAI, Hugging Face, ChromaDB, PromptFlow, and AWS Bedrock to create chatbots, summaries, semantic search, and intelligent automation. I participate in the full software lifecycle, grounding AI capabilities in solid software design and observable business impact.…Hello, I’m Narasimha Arepalli, a senior AI/ML & Generative AI Engineer with 10+ years delivering scalable, production-grade AI and data solutions across telecom, government, healthcare, and enterprise domains. I design, build, and deploy end-to-end AI/ML and Generative AI systems using cloud-native architectures across Azure, AWS, and GCP, with hands-on experience with LLMs such as GPT, LLaMA, BERT, and Claude. I’ve built conversational AI, document intelligence platforms, and retrieval-augmented generation (RAG) pipelines, and I frequently leverage LangChain, OpenAI, Hugging Face, ChromaDB, PromptFlow, and AWS Bedrock to create chatbots, summaries, semantic search, and intelligent automation. I participate in the full software lifecycle, grounding AI capabilities in solid software design and observable business impact.

Narasimha Arepalli

AI Engineer, Data Scientist, AI Developer, +3

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Hello, I’m Narasimha Arepalli, a senior AI/ML & Generative AI Engineer with 10+ years delivering scalable, production-grade AI and data solutions across telecom, government, healthcare, and enterprise domains. I design, build, and deploy end-to-end AI/ML and Generative AI systems using cloud-native architectures across Azure, AWS, and GCP, with hands-on experience with LLMs such as GPT, LLaMA, BERT, and Claude. I’ve built conversational AI, document intelligence platforms, and retrieval-augmented generation (RAG) pipelines, and I frequently leverage LangChain, OpenAI, Hugging Face, ChromaDB, PromptFlow, and AWS Bedrock to create chatbots, summaries, semantic search, and intelligent automation. I participate in the full software lifecycle, grounding AI capabilities in solid software design and observable business impact.…Hello, I’m Narasimha Arepalli, a senior AI/ML & Generative AI Engineer with 10+ years delivering scalable, production-grade AI and data solutions across telecom, government, healthcare, and enterprise domains. I design, build, and deploy end-to-end AI/ML and Generative AI systems using cloud-native architectures across Azure, AWS, and GCP, with hands-on experience with LLMs such as GPT, LLaMA, BERT, and Claude. I’ve built conversational AI, document intelligence platforms, and retrieval-augmented generation (RAG) pipelines, and I frequently leverage LangChain, OpenAI, Hugging Face, ChromaDB, PromptFlow, and AWS Bedrock to create chatbots, summaries, semantic search, and intelligent automation. I participate in the full software lifecycle, grounding AI capabilities in solid software design and observable business impact.

Available to hire

Hello, I’m Narasimha Arepalli, a senior AI/ML & Generative AI Engineer with 10+ years delivering scalable, production-grade AI and data solutions across telecom, government, healthcare, and enterprise domains. I design, build, and deploy end-to-end AI/ML and Generative AI systems using cloud-native architectures across Azure, AWS, and GCP, with hands-on experience with LLMs such as GPT, LLaMA, BERT, and Claude. I’ve built conversational AI, document intelligence platforms, and retrieval-augmented generation (RAG) pipelines, and I frequently leverage LangChain, OpenAI, Hugging Face, ChromaDB, PromptFlow, and AWS Bedrock to create chatbots, summaries, semantic search, and intelligent automation. I participate in the full software lifecycle, grounding AI capabilities in solid software design and observable business impact.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Language

English

Fluent

Japanese

Advanced

Work Experience

AI/ML Engineer at Verizon

October 1, 2023 - Present

Enterprise forecasting platform built to improve inventory planning and reduce wastage by moving from historical reporting to predictive analytics. Led end-to-end AI solution development, delivering forward-looking insights that improved forecast accuracy, enabled proactive decision-making, and established a scalable foundation for enterprise rollout.

AI/ Machine Learning Engineer at State of MI

April 1, 2020 - September 1, 2023

Large-scale government analytics platform delivering AI-driven automation, NLP-based insight extraction, and predictive analytics to automate workflows and modernize statewide data operations.

ML/Data Analyst at Charter Communications

January 1, 2018 - March 1, 2020

Real-time fraud detection and anomaly analytics system for large-scale transactional data, building ML models and pipelines to improve fraud detection and operational decision-making.

Data Analyst at Synchrony Financial

March 1, 2015 - February 1, 2016

Financial analytics and reporting platform; implemented predictive models and automation for improving decision-making and operational efficiency.

AI/Machine Learning Engineer at State of Michigan

April 1, 2020 - September 30, 2023

Designed, developed, and deployed end-to-end ML solutions on Microsoft Azure for statewide analytics and automation. Built supervised learning pipelines (KNN, Logistic Regression, Random Forest, Gradient Boosting, XGBoost) with PCA-based feature selection, and used Azure ML Designer and Automated ML to rapidly prototype and productionize models. Executed advanced statistical analyses (hypothesis testing, t-tests, ANOVA) to validate data integrity and model effectiveness. Developed NLP pipelines (spaCy, NLTK, Transformers) for tokenization, sentiment, and classification; built deep learning models with BERT/Transformers using PyTorch/TensorFlow; engineered LLM-based architectures with embeddings to support semantic understanding. Integrated Azure OpenAI for automation workflows and implemented Retrieval-Augmented Generation (RAG) using Azure Cognitive Search and vector databases. Conducted A/B testing for chatbot/NLP applications, built interactive analytics dashboards (Azure Databricks

Data Analyst at Intone Networks

March 1, 2015 - February 29, 2016

Data analytics and reporting platform focused on financial operations. Designed and implemented a relational database using Microsoft Access, created tables, data types, and schemas, and executed SQL queries to retrieve and manipulate data. Built Excel-based dashboards and visualizations, performed data validation, and automated repetitive data preparation tasks. Designed ETL workflows to transfer web server logs to Google Cloud Storage, built automated text data cleaning tools with Python/Pandas, and leveraged Google Cloud ML tools (Vertex AI) for model training, validation, and deployment. Collected and integrated customer feedback data from social media, surveys, and emails to generate actionable insights; Produced Looker Studio/Matplotlib visualizations and reports; Conducted hypothesis testing and Chi-square tests to support decision-making.

ML Engineer / Data Analyst at Synchrony Financial

March 1, 2016 - August 31, 2017

Led design and implementation of ML models using Python, Scikit-learn, and TensorFlow; deployed on AWS SageMaker for scalable training and inference. Built scalable ML pipelines for fraud detection and anomaly analytics; implemented real-time processing with GPU-accelerated computing; designed ML workflows using AWS Lambda, SageMaker, and CloudFormation; integrated AWS Glue for data preprocessing; performed hyperparameter tuning with SageMaker; established MLOps with CodePipeline and SageMaker for CI/CD and monitoring; leveraged S3 for data storage and retrieval; collaborated with analytics and policy teams to translate requirements into scalable AI solutions.