Available to hire
I’m a GenAI Engineer with a passion for designing and deploying production-grade AI solutions using large language models and cloud-native platforms. I enjoy exploring AI-driven solutions, staying updated with GenAI advancements, and turning business problems into scalable, secure AI systems through end-to-end pipelines, API integrations, and robust MLOps practices.
I thrive in collaborative settings, translating stakeholder needs into practical AI/ML applications, and I’m committed to delivering high-quality, interpretable results while championing responsible AI.
Experience Level
Expert
Expert
Expert
Expert
Expert
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Expert
Expert
Expert
Expert
Expert
Expert
Expert
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Expert
Expert
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Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate
Language
English
Fluent
Work Experience
Gen AI Engineer at State Farm
January 1, 2025 - PresentDesigned and deployed Generative AI applications using OpenAI GPT-4 and Hugging Face Transformers integrated with LangChain for advanced prompt engineering and RAG. Built scalable LLM-powered workflows on AWS SageMaker for enterprise use cases. Developed RAG pipelines using Amazon OpenSearch, S3, and FAISS for vector similarity search from private datasets. Created full-stack apps (React.js frontend, FastAPI backend) integrated with AWS Lambda, API Gateway, DynamoDB, and RDS for serverless orchestration. Engineered serverless LLM inference workflows with AWS Step Functions and Lambda, orchestrating multi-agent tasks via LangChain. Containerized services with Docker and deployed on Amazon EKS with CI/CD pipelines. Integrated AWS Cognito for secure multi-tenant authorization. Leveraged AWS Textract and Comprehend for document data extraction feeding GPT-4 workflows. Built real-time chatbot interfaces with streaming GPT responses via WebSockets and React. Implemented security and complian
AI/ML Engineer at Health Care Service Corporation
December 31, 2024 - September 4, 2025Designed, developed, and deployed ML models using Azure Machine Learning with automated pipelines and hyperparameter tuning, improving prediction accuracy. Built end-to-end workflows on Azure Databricks for large-scale data processing using Spark, Python, and MLflow. Developed scalable ML APIs on Azure Functions and AKS for real-time and batch inference. Created data ingestion pipelines using Azure Data Factory and Synapse Analytics integrating diverse sources into Azure Data Lake. Utilized Azure Cognitive Services for NLP and vision enhancements. Engineered deployment pipelines via Azure DevOps for CI/CD. Applied advanced ML algorithms like XGBoost and Neural Networks to solve business problems such as churn prediction and sales forecasting. Ensured Responsible AI compliance and data privacy. Developed Power BI dashboards to communicate insights and monitored models with Azure Monitor.
Data Scientist at IBM
June 30, 2023 - September 4, 2025Collected, cleaned, and analyzed large datasets using Python and SQL to identify trends for business decision-making. Developed predictive models using Random Forest, XGBoost, and Logistic Regression for classification and regression tasks. Built data pipelines and automated ETL with Apache Airflow and SQL improving data quality. Visualized data trends using Matplotlib, Seaborn, Tableau, and Power BI dashboards. Conducted A/B testing and statistical analysis to evaluate business initiatives. Collaborated with engineering and product teams to integrate data-driven models into production workflows. Applied NLP techniques with NLTK and spaCy for sentiment analysis and topic modeling. Implemented model monitoring and performance tracking with MLflow. Explored big data tools such as Spark and Hadoop for distributed data processing. Ensured data governance and compliance for privacy and security.
Gen AI Engineer at State Farm
January 1, 2025 - PresentDesigned and deployed Generative AI applications using OpenAI GPT-4 and Hugging Face Transformers integrated with LangChain for prompt engineering and retrieval-augmented generation (RAG). Built scalable, secure LLM-powered workflows on AWS SageMaker for model training, fine-tuning, and endpoint deployment tailored to enterprise use cases. Developed RAG pipelines utilizing Amazon OpenSearch, Amazon S3, and FAISS for vector similarity search, enabling context-rich responses from private datasets. Created full-stack applications with React.js frontend and FastAPI/Python backend, integrating AWS services such as AWS Lambda, API Gateway, DynamoDB, and RDS for storage and serverless orchestration. Engineered serverless LLM inference workflows with AWS Step Functions and Lambda, orchestrating multi-agent tasks with LangChain tool usage. Containerized GenAI microservices with Docker and deployed on Amazon EKS with CI/CD pipelines via AWS CodePipeline and GitHub Actions. Implemented secure aut
AI/ML Engineer at Health Care Service Corporation
December 1, 2024 - October 3, 2025Designed, developed, and operationalized ML models using Azure Machine Learning with automated ML pipelines and hyperparameter tuning. Built end-to-end ML workflows on Azure Databricks for large-scale data processing, feature engineering, and model training with MLflow for experiment tracking. Developed scalable inference APIs using Azure Functions and AKS for real-time and batch predictions. Created data ingestion/transformation pipelines with Azure Data Factory and Azure Synapse Analytics, integrating data into an Azure Data Lake. Leveraged Azure Cognitive Services (Computer Vision, Text Analytics, Language Understanding) to enhance AI applications. Built deployment pipelines with Azure DevOps for CI/CD, enabling model versioning and automated releases. Applied feature selection, dimensionality reduction, and advanced ML algorithms (XGBoost, Random Forest, Neural Networks) to churn prediction and sales forecasting. Collaborated to ensure Responsible AI, privacy, and security, and bui
Data Scientist at IBM
June 1, 2023 - October 3, 2025Collected, cleaned, and analyzed large datasets with Python (Pandas, NumPy) and SQL to identify trends and actionable insights. Developed predictive models using Random Forest, Gradient Boosting (XGBoost), and Logistic Regression for classification and regression problems. Built data pipelines and automated ETL with Apache Airflow; visualized trends with Matplotlib, Seaborn, and dashboards. Conducted A/B testing and statistical analysis; collaborated with engineering to integrate models into production. Explored NLP techniques (sentiment analysis, topic modeling) using NLTK and spaCy and implemented model monitoring with MLflow. Ensured data governance and privacy; worked with big data tools like Spark/Hadoop when needed.
Gen AI Engineer at State Farm
January 1, 2025 - PresentDesigned and deployed Generative AI applications using OpenAI GPT-4 and Hugging Face Transformers integrated with LangChain for advanced prompt engineering and retrieval-augmented generation (RAG). Built scalable, secure LLM-powered workflows on AWS SageMaker for model training, fine-tuning, and endpoint deployment tailored to enterprise use cases. Developed RAG pipelines utilizing Amazon OpenSearch, Amazon S3, and FAISS for vector similarity search, enabling context-rich responses from private datasets. Created full-stack applications with React.js frontend and FastAPI/Python backend, integrating AWS services such as AWS Lambda, API Gateway, DynamoDB, and RDS (PostgreSQL) for storage and serverless orchestration. Engineered serverless LLM inference workflows with AWS Step Functions and AWS Lambda, orchestrating multi-agent tasks with LangChain tool usage. Containerized GenAI microservices using Docker and deployed on Amazon EKS (Elastic Kubernetes Service) with CI/CD pipelines via AWS
AI/ML Engineer at Health Care Service Corporation
December 31, 2024 - October 3, 2025Designed, developed, and deployed machine learning models using Azure Machine Learning (AML) service, improving prediction accuracy via automated ML pipelines and hyperparameter tuning. Built end-to-end ML workflows on Azure Databricks for large-scale data processing, feature engineering, and model training using Spark, Python (PySpark), and MLflow for experiment tracking. Developed scalable ML APIs using Azure Functions and Azure Kubernetes Service (AKS) for real-time inference and batch processing. Created data ingestion and transformation pipelines using Azure Data Factory and Azure Synapse Analytics, integrating diverse data sources into centralized Azure Data Lake. Leveraged Azure Cognitive Services (Computer Vision, Text Analytics, and Language Understanding) to enhance AI apps with pre-built NLP and vision models. Engineered deployment pipelines using Azure DevOps for CI/CD, ensuring seamless model versioning, testing, and automated releases. Applied feature selection, dimension
Data Scientist at IBM
June 30, 2023 - October 3, 2025Collected, cleaned, and analyzed large datasets using Python (Pandas, NumPy) and SQL, identifying trends and providing actionable insights. Developed predictive models using Random Forest, Gradient Boosting (XGBoost), and Logistic Regression. Built data pipelines and automated ETL with Apache Airflow and SQL, improving data accessibility and quality. Visualized data trends with Matplotlib, Seaborn, and Tableau/Power BI dashboards. Conducted A/B testing and statistical analysis to evaluate initiatives and optimize features. Collaborated with engineering and product teams to deploy data-driven models to production and ensure governance and privacy.
Gen AI Engineer at State Farm
January 1, 2025 - PresentDesigned and deployed Generative AI applications leveraging OpenAI GPT-4 and Hugging Face Transformers with LangChain for advanced prompt engineering and retrieval-augmented generation (RAG). Built scalable LLM-powered workflows on AWS SageMaker for model training, fine-tuning, and enterprise-endpoint deployment. Implemented RAG pipelines using OpenSearch, S3, and FAISS for context-rich responses from private datasets. Delivered full-stack apps with a React frontend and FastAPI backend, integrating AWS Lambda, API Gateway, DynamoDB, and RDS. Orchestrated multi-agent tasks via LangChain and serverless inference using Step Functions. Containerized microservices with Docker and deployed on Amazon EKS with CI/CD via CodePipeline and GitHub Actions. Implemented secure multi-tenant authentication with AWS Cognito and leveraged Textract/Comprehend for document data extraction feeding GPT-4 workflows. Built real-time chatbot interfaces with streaming GPT responses over WebSockets. Enforced sec
AI/ML Engineer at Health Care Service Corporation
December 1, 2024 - October 22, 2025Designed, developed, and deployed ML models using Azure Machine Learning with automated pipelines and hyperparameter tuning. Built end-to-end ML workflows on Azure Databricks for large-scale data processing, feature engineering, and model training with Spark, PySpark, and MLflow. Deployed scalable ML APIs via Azure Functions and AKS for real-time inference and batch processing. Created data ingestion/transformation pipelines with Azure Data Factory and Azure Synapse Analytics, consolidating data into a centralized Azure Data Lake. Leveraged Azure Cognitive Services for Computer Vision, Text Analytics, and Language Understanding. Implemented CI/CD using Azure DevOps; applied feature selection, dimensionality reduction, and models (XGBoost, Random Forest, Neural Networks). Ensured Responsible AI compliance, data privacy, and security; built Power BI dashboards; monitored models with Azure Monitor and Application Insights.
Data Scientist at IBM
June 1, 2023 - October 22, 2025Collected, cleaned, and analyzed large datasets using Python (Pandas, NumPy) and SQL to identify trends and actionable insights. Developed predictive models using Random Forest, Gradient Boosting (XGBoost), and Logistic Regression. Built data pipelines and automated ETL with Apache Airflow; visualized trends with Matplotlib/Seaborn and dashboards in Tableau/Power BI. Conducted A/B tests and statistical analyses to optimize initiatives. Collaborated with engineering and product teams to deploy data-driven models into production, applied NLP techniques (sentiment analysis, topic modeling) using NLTK and spaCy, and implemented model monitoring with MLflow. Ensured data governance and security throughout the lifecycle.
Gen AI Engineer at State Farm
January 1, 2025 - November 7, 2025Designed and deployed Generative AI applications using OpenAI GPT-4 and Hugging Face Transformers integrated with LangChain for prompt engineering and retrieval-augmented generation (RAG). Built scalable, secure LLM-powered workflows on AWS SageMaker for model training, fine-tuning, and endpoint deployment. Developed RAG pipelines utilizing Amazon OpenSearch, Amazon S3, and FAISS for vector similarity search, enabling context-rich responses from private datasets. Created full-stack applications with React.js frontend and FastAPI/Python backend, integrating AWS services such as Lambda, API Gateway, DynamoDB, and RDS for storage and serverless orchestration. Engineered serverless LLM inference workflows with AWS Step Functions and Lambda, orchestrating multi-agent tasks with LangChain tool usage. Containerized GenAI microservices using Docker and deployed on Amazon EKS with CI/CD pipelines via AWS CodePipeline and GitHub Actions. Integrated AWS Cognito for secure user authentication and
AI/ML Engineer at Health Care Service Corporation
December 31, 2024 - December 31, 2024Designed, developed, and deployed machine learning models using Azure Machine Learning (AML) service, leveraging automated ML pipelines and hyperparameter tuning. Built end-to-end ML workflows on Azure Databricks for large-scale data processing, feature engineering, and model training using Spark, Python (PySpark), and MLflow for experiment tracking. Developed and operationalized scalable ML APIs using Azure Functions and AKS for real-time inference and batch processing. Created data ingestion and transformation pipelines using Azure Data Factory and Azure Synapse Analytics, integrating diverse data sources into centralized Azure Data Lake. Utilized Azure Cognitive Services (Computer Vision, Text Analytics, and Language Understanding) to enhance AI applications with pre-built NLP and vision models. Engineered deployment pipelines using Azure DevOps for CI/CD, ensuring seamless model versioning, testing, and automated releases. Applied feature selection, dimensionality reduction, and ad
Data Scientist at IBM
June 30, 2023 - June 30, 2023Collected, cleaned, and analyzed large datasets using Python (Pandas, NumPy) and SQL to identify trends and actionable insights for business decision-making. Developed predictive models using machine learning algorithms such as Random Forest, Gradient Boosting (XGBoost), and Logistic Regression to solve classification and regression problems. Built data pipelines and automated ETL processes with Apache Airflow and SQL, improving data accessibility and quality across teams. Visualized complex data trends using Matplotlib, Seaborn, and Tableau/Power BI dashboards to communicate findings effectively. Conducted A/B testing and statistical analysis to evaluate the impact of business initiatives and optimize product features. Collaborated with engineering and product teams to integrate data-driven models into production systems and business workflows. Applied NLP techniques like sentiment analysis and topic modeling with NLTK and spaCy. Implemented model monitoring and performance tracking w
AI/ML Engineer at Health Care Service Corporation
November 1, 2023 - December 31, 2024Developed and deployed end-to-end AI/ML solutions on Microsoft Azure for predictive analytics, NLP, computer vision, and Generative AI. Built and operationalized ML pipelines with Azure ML (data ingestion, feature engineering, model training, validation, deployment, monitoring). Applied supervised/unsupervised learning (Scikit-learn, TensorFlow, PyTorch, XGBoost); integrated GenAI/ML with APIs, microservices, and event-driven architectures. Managed data pipelines with Azure Data Factory, Synapse, ADLS Gen2, and Databricks; profiled, cleansed, and analyzed data with Pandas/NumPy; deployed ML models with Scikit-learn. Implemented MLOps with Azure ML, MLflow, Git, and Azure DevOps; integrated Azure OpenAI Service with prompt engineering, embeddings, and RAG using Azure Cognitive Search. Monitored performance with Azure Monitor and Application Insights; produced automated Power BI reporting.
Data Scientist at IBM
January 1, 2021 - June 30, 2023Developed, trained, and evaluated ML models with Python, Scikit-learn, XGBoost, TensorFlow, and PyTorch; deployed models on Amazon SageMaker. Tuned parameters via grid search and cross-validation; built deep learning algorithms with Keras. Leveraged Pandas, NumPy, Seaborn, SciPy, Matplotlib, NLTK for a range of ML tasks (regression, classification, clustering). Built end-to-end data science workflows with AWS S3, Glue, Athena, Redshift, and RDS; utilized Spark and R for scalable analyses. Applied ML/AI techniques to deliver scalable, data-driven business insights; automated data cleaning and feature engineering; deployed containerized applications with Docker and Nagios-based monitoring; visualized results with Matplotlib/Seaborn.
Education
Master's in Computer Science at Cleveland State University
August 1, 2023 - May 1, 2025Bachelor's in Computer Science and Engineering at Vignan’s Institute of Information Technology
August 1, 2018 - June 1, 2022Master's in Computer Science at Cleveland State University
January 11, 2030 - May 1, 2025Bachelor's in Computer Science and Engineering at Vignan’s Institute of Information Technology
January 11, 2030 - June 1, 2022Master’s in Computer Science at Cleveland State University
January 11, 2030 - May 1, 2025Bachelor’s in Computer Science and Engineering at Vignan’s Institute of Information Technology
January 11, 2030 - June 1, 2022Master’s in Computer Science at Cleveland State University
January 11, 2030 - May 1, 2025Bachelor’s in Computer Science and Engineering at Vignan’s Institute of Information Technology
January 11, 2030 - June 1, 2022Master of Science in Computer Science at Cleveland State University
January 11, 2030 - May 1, 2025Bachelor of Science in Computer Science and Engineering at Vignan’s Institute of Information Technology
January 11, 2030 - June 1, 2022Master's in Computer Science at Cleveland State University
January 11, 2030 - May 1, 2025Bachelor's in Computer Science and Engineering at Vignan's Institute of Information Technology
January 11, 2030 - June 1, 2022Qualifications
CCNAv7: Introduction to Networks – Cisco
January 11, 2030 - September 4, 2025PCAP: Python Programming – Cisco NetAcad & Python Institute
January 11, 2030 - September 4, 2025Java Programming – Coursera (Board Infinity)
January 11, 2030 - September 4, 2025CCNA Introduction to Networks
January 11, 2030 - October 3, 2025PCAP: Python Programming
January 11, 2030 - October 3, 2025Java Programming
January 11, 2030 - October 3, 2025CCNAv7: Introduction to Networks
January 11, 2030 - October 3, 2025PCAP: Python Programming
January 11, 2030 - October 3, 2025Java Programming
January 11, 2030 - October 3, 2025CCNA: Introduction to Networks
January 11, 2030 - October 22, 2025PCAP: Python Programming
January 11, 2030 - October 22, 2025Java Programming
January 11, 2030 - October 22, 2025Electronic Arts Software Engineering virtual experience program on Forage
January 11, 2030 - October 22, 2025CCNA: Introduction to Networks
January 11, 2030 - November 7, 2025PCAP: Python Programming
January 11, 2030 - November 7, 2025Java Programming
January 11, 2030 - November 7, 2025Electronic Arts Software Engineering virtual experience program
January 11, 2030 - November 7, 2025CCNAv7: Introduction to Networks
January 11, 2030 - February 5, 2026PCAP: Python Programming
January 11, 2030 - February 5, 2026Java Programming
January 11, 2030 - February 5, 2026Electronic Arts Software Engineering virtual experience program on Forage
June 1, 2025 - February 5, 2026Industry Experience
Healthcare, Software & Internet, Financial Services, Professional Services, Other, Computers & Electronics
Experience Level
Expert
Expert
Expert
Expert
Expert
Expert
Expert
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Expert
Expert
Expert
Expert
Expert
Expert
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Expert
Expert
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Expert
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Expert
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Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate
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