Agentic AI Engineer at HCA Healthcare

Built and enhanced a cloud-native enterprise AI Agent Platform for SDLC automation and engineering knowledge assistance. Implemented FastAPI microservices, PostgreSQL schema/versioned migrations, and scalable asynchronous request handling with Google Cloud Pub/Sub. Developed feedback management routed to Azure DevOps work items to reduce manual triage. Integrated enterprise LLM services with prompt orchestration and RAG/vector search to answer from internal technical knowledge. Designed secure authentication/authorization using Azure AD and Google Identity (JWT, RBAC, on-behalf-of flows). Delivered a React UI with an auth BFF layer and improved production readiness using Docker, OpenAPI/Swagger, Pytest automation, and Azure DevOps CI/CD (80%+ test coverage).

Gen AI Engineer at JPMorgan Chase & Co

Architected and deployed a real-time hybrid recommendation engine and an agentic AI framework on Azure. Led a 40% lift in transaction value and a 50% increase in offer utilization using Azure Databricks and Data Factory. Built LangChain/LangGraph agentic workflows on AKS to automate root-cause analysis and anomaly detection (40% reduction in resolution time). Developed RAG with Azure Cognitive Search vector search and FAISS, improving retrieval speed/accuracy by 25%. Implemented NL-to-SQL prompt engineering, and LLM monitoring/tracing using Langfuse and Azure Promptflow to reduce hallucinations and speed debugging. Established governance with MLflow, Docker, AKS, and Azure DevOps, including token-cost monitoring and inference optimizations via quantization/pruning.

Gen AI Engineer at Intel

Led NexGen MarTech initiative to build/fine-tune generative AI chatbots and regulatory-PDF parsing platforms for pharmaceutical clients. Produced $5M+ incremental revenue via AI-driven campaign automation and improved bot response speeds (~3×). Implemented conversational bots on AKS using CrewAI orchestration for bookings/inquiries. Built regulatory PDF parsing and literature assistants by fine-tuning GPT/BERT-family (BioBERT, ClinicalBERT) in PyTorch, reducing medical writer hours (~35%). Trained BioBERT NER for adverse events/dosages/compound extraction. Implemented MLflow pipelines for training/deployment/monitoring, reducing iteration cycles (~40%). Evaluated models with PyTorch benchmarks, improving accuracy (~20%). Delivered similarity search workflows using Azure Cognitive AI + vector embeddings and built ML models for CLTV and LSTM-based sensor failure prediction. Created full-stack React + FastAPI apps with dashboards/backends/DevOps pipelines and led Tealium Customer Data Hu

Gen AI Engineer (Chatbot Solution & Regulatory-PDF Parsing Platform) at Intel

Led the NexGen MarTech initiative building and fine-tuning GenAI chatbots and regulatory PDF parsers for pharmaceutical clients. Generated over $5M in incremental revenue via AI-driven campaign automation. Improved conversational bot response speeds by 3× using CrewAI orchestration on AKS. Fine-tuned transformer models (GPT and BERT-family including BioBERT/ClinicalBERT) in PyTorch for regulatory extraction and clinical Q&A, reducing medical writer hours by 35%. Implemented MLflow pipelines for training/deployment/monitoring and benchmarked models to improve accuracy by ~20%. Built vector embedding similarity search for faster retrieval and engineered additional predictive models (e.g., CLTV) to support segmentation and engagement improvements. Delivered full-stack React + FastAPI dashboards and APIs with DevOps pipelines; oversaw Tealium Customer Data Hub ingestion architecture and governance compliance.

AI, ML Engineer / Data Scientist at Cigna

Developed real-time fraud detection and NLP automation platforms. Built streaming fraud detection models using tree-based methods (XGBoost, Random Forest, Gradient Boosting, Logistic Regression), preventing ~$1.3M in fraudulent losses. Implemented scalable ETL from SQL Server to Hadoop (HDFS, Hive, Pig) and used Azure Databricks/Spark for distributed feature engineering/model training. Built NLP pipelines with SpaCy/NLTK for document classification and sensitive-data detection, integrating LLM summarization to improve accuracy (~27%). Automated CI/CD using Jenkins, Docker, AKS. Improved robustness using SMOTE/advanced resampling for class imbalance, reducing false positives. Added PCA/t-SNE and feature engineering for modeling, built multiple ML models (SVM, KNN, ensembles), and automated data-subject request processing with Snowflake and Adobe Analytics Privacy API. Migrated systems to Azure, set up Snowflake warehouses, and contributed transformer prototypes for renewable-energy use

AI, ML Engineer / Data Scientist (Real-Time Fraud Detection & NLP Automation Platform) at Cigna

Developed and operationalized real-time fraud detection and NLP analytics pipelines for healthcare transactions. Built streaming fraud detection models and prevented $1.3M in fraudulent losses. Enhanced data extraction accuracy by 27% with integrated LLM-driven alerts. Implemented NLP pipelines with SpaCy/NTLK for classification and sensitive-data detection and added LLM summarization. Built scalable ETL from SQL Server to Hadoop HDFS using Hive and Pig, and used Azure Databricks/Spark for distributed feature engineering and training on multi-terabyte datasets. Automated CI/CD with Jenkins/Docker/AKS and improved robustness using SMOTE/resampling for class imbalance. Also automated data-subject request processing integrating Snowflake and an analytics privacy API, and migrated on-prem systems to Azure with Snowflake data warehouses.

Data Scientist at Reliance Industries

Built churn prediction and dynamic pricing optimization for e-commerce. Led Agile transformation company-wide. Directed Hot Deals/Flash Deals campaigns using A/B and hypothesis testing, prioritizing strategies generating $50M+ incremental revenue. Developed real-time churn prediction using AFT Survival models for high-risk segments and recommended interventions, lifting delivery-partner retention (~13%). Created pricing analytics framework with price elasticity and Random Forests, increasing average order value (~12%) and profit (~8%). Architected continuous delivery pipeline with Docker and Nexus. Implemented AWS Boto3-based ETL from S3 events into Snowflake and Postgres and automated Adobe Analytics ingestion. Added Snowflake stored procedures to detect and salt-hash PII for CCPA compliance. Integrated Databricks workflows for distributed feature engineering and built dashboards with Matplotlib/ggplot2.

Data Scientist (Churn-Prediction & Dynamic Pricing Optimization) at Reliance Industries

Drove customer retention and pricing optimization using survival-analysis churn modeling and dynamic price-elasticity frameworks for e-commerce campaigns. Delivered a 13% lift in delivery-partner retention using AFT Survival models and improved average order value by 12% via A/B-tested flash deals. Built pricing-analytics frameworks combining price elasticity modeling and Random Forests to optimize delivery fees and improve profit. Led Agile transformation across business and technology teams. Architected continuous delivery pipelines with Docker and Nexus v3. Engineered ETL using AWS (Boto3 for S3/SQS/Secrets Manager) to ingest events into Snowflake and Postgres. Automated Adobe Analytics ingestion, implemented PII detection/salt-hash stored procedures for CCPA compliance, and integrated Databricks workflows for distributed feature engineering. Created dashboards to translate insights into profitability gains.