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I am a Generative AI Engineer / Machine Learning Engineer with 10+ years of experience building production-grade AI solutions across banking, healthcare, retail, and transportation. I specialize in Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG), delivering grounded, auditable AI systems for regulated enterprise environments. I have hands-on experience with Azure OpenAI and have built RAG pipelines using Azure AI Search, FAISS, and Elasticsearch for document intelligence and policy reasoning. I bring strong ML Engineering expertise in feature engineering, time-series forecasting, anomaly detection, and predictive modeling, with proficiency in Python ecosystems such as Scikit-learn, XGBoost, LightGBM, ARIMA, and LSTM. I have delivered end-to-end ML and GenAI pipelines with data ingestion, model training, deployment, and monitoring in production. My background spans multi-cloud platforms (Azure primary, with AWS and GCP for ML/GenAI), Conversational AI using Vertex AI, Dialogflow, and CCAI, and data engineering with Spark, Kafka, and streaming. I build API-driven AI services with FastAPI/Flask, containerized with Docker and AKS, and I apply MLOps/GenAIOps practices using MLflow and CI/CD to ensure scalable, auditable deployments.…I am a Generative AI Engineer / Machine Learning Engineer with 10+ years of experience building production-grade AI solutions across banking, healthcare, retail, and transportation. I specialize in Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG), delivering grounded, auditable AI systems for regulated enterprise environments. I have hands-on experience with Azure OpenAI and have built RAG pipelines using Azure AI Search, FAISS, and Elasticsearch for document intelligence and policy reasoning. I bring strong ML Engineering expertise in feature engineering, time-series forecasting, anomaly detection, and predictive modeling, with proficiency in Python ecosystems such as Scikit-learn, XGBoost, LightGBM, ARIMA, and LSTM. I have delivered end-to-end ML and GenAI pipelines with data ingestion, model training, deployment, and monitoring in production. My background spans multi-cloud platforms (Azure primary, with AWS and GCP for ML/GenAI), Conversational AI using Vertex AI, Dialogflow, and CCAI, and data engineering with Spark, Kafka, and streaming. I build API-driven AI services with FastAPI/Flask, containerized with Docker and AKS, and I apply MLOps/GenAIOps practices using MLflow and CI/CD to ensure scalable, auditable deployments.

Raghavendra Kare

AI Engineer, Data Scientist, Developer, +6

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I am a Generative AI Engineer / Machine Learning Engineer with 10+ years of experience building production-grade AI solutions across banking, healthcare, retail, and transportation. I specialize in Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG), delivering grounded, auditable AI systems for regulated enterprise environments. I have hands-on experience with Azure OpenAI and have built RAG pipelines using Azure AI Search, FAISS, and Elasticsearch for document intelligence and policy reasoning. I bring strong ML Engineering expertise in feature engineering, time-series forecasting, anomaly detection, and predictive modeling, with proficiency in Python ecosystems such as Scikit-learn, XGBoost, LightGBM, ARIMA, and LSTM. I have delivered end-to-end ML and GenAI pipelines with data ingestion, model training, deployment, and monitoring in production. My background spans multi-cloud platforms (Azure primary, with AWS and GCP for ML/GenAI), Conversational AI using Vertex AI, Dialogflow, and CCAI, and data engineering with Spark, Kafka, and streaming. I build API-driven AI services with FastAPI/Flask, containerized with Docker and AKS, and I apply MLOps/GenAIOps practices using MLflow and CI/CD to ensure scalable, auditable deployments.…I am a Generative AI Engineer / Machine Learning Engineer with 10+ years of experience building production-grade AI solutions across banking, healthcare, retail, and transportation. I specialize in Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG), delivering grounded, auditable AI systems for regulated enterprise environments. I have hands-on experience with Azure OpenAI and have built RAG pipelines using Azure AI Search, FAISS, and Elasticsearch for document intelligence and policy reasoning. I bring strong ML Engineering expertise in feature engineering, time-series forecasting, anomaly detection, and predictive modeling, with proficiency in Python ecosystems such as Scikit-learn, XGBoost, LightGBM, ARIMA, and LSTM. I have delivered end-to-end ML and GenAI pipelines with data ingestion, model training, deployment, and monitoring in production. My background spans multi-cloud platforms (Azure primary, with AWS and GCP for ML/GenAI), Conversational AI using Vertex AI, Dialogflow, and CCAI, and data engineering with Spark, Kafka, and streaming. I build API-driven AI services with FastAPI/Flask, containerized with Docker and AKS, and I apply MLOps/GenAIOps practices using MLflow and CI/CD to ensure scalable, auditable deployments.

Available to hire

I am a Generative AI Engineer / Machine Learning Engineer with 10+ years of experience building production-grade AI solutions across banking, healthcare, retail, and transportation. I specialize in Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG), delivering grounded, auditable AI systems for regulated enterprise environments. I have hands-on experience with Azure OpenAI and have built RAG pipelines using Azure AI Search, FAISS, and Elasticsearch for document intelligence and policy reasoning.

I bring strong ML Engineering expertise in feature engineering, time-series forecasting, anomaly detection, and predictive modeling, with proficiency in Python ecosystems such as Scikit-learn, XGBoost, LightGBM, ARIMA, and LSTM. I have delivered end-to-end ML and GenAI pipelines with data ingestion, model training, deployment, and monitoring in production. My background spans multi-cloud platforms (Azure primary, with AWS and GCP for ML/GenAI), Conversational AI using Vertex AI, Dialogflow, and CCAI, and data engineering with Spark, Kafka, and streaming. I build API-driven AI services with FastAPI/Flask, containerized with Docker and AKS, and I apply MLOps/GenAIOps practices using MLflow and CI/CD to ensure scalable, auditable deployments.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Scala

Intermediate

Language

English

Fluent

Work Experience

Generative AI Engineer at Citizens Financial Group

January 1, 2023 - November 24, 2025

Designed and deployed a Generative AI-powered financial document intelligence platform, leveraging fine-tuned LLMs (GPT, LLaMA) to automate credit risk analysis, fraud detection, and compliance checks. Implemented Retrieval-Augmented Generation (RAG) pipelines with FAISS, Pinecone, and ElasticSearch for domain-specific knowledge retrieval, improving accuracy of financial reporting and document summarization. Built end-to-end ML pipelines on AWS SageMaker and Glue for ingesting, cleaning, and analyzing structured/unstructured banking datasets. Fine-tuned domain-specific LLMs using LoRA, PEFT, and instruction tuning for regulatory reporting, KYC/AML verification, and internal knowledge search. Implemented explainable AI frameworks; ensured compliance. Optimized LLM inference with AWS Inferentia and SageMaker Neo for low-latency apps. Developed ETL and real-time data pipelines using Apache Spark, Glue, and Kafka. Applied data augmentation to improve model robustness. Established MLOps pra

Generative AI Engineer / Data Scientist at Centene Corporation

December 1, 2022 - December 1, 2022

Designed and implemented Generative AI–based healthcare virtual assistant (GPT-3/transformers) to automate claims inquiries, benefit explanations, and provider interactions. Built Retrieval-Augmented Generation (RAG) pipelines with FAISS and Elasticsearch for knowledge retrieval from policy documents, clinical guidelines, and member communication archives. Built NLP/NLU models for intent detection, entity recognition, and contextual response generation. Automated summarization workflows for clinical notes, authorization forms, and case management reports. Implemented speech-to-text and text-to-speech to support multilingual member engagement. Built end-to-end ML pipelines on Google Cloud Vertex AI and BigQuery; automated data ingestion with Airflow and Spark. Implemented MLOps with MLflow; ensured HIPAA compliance; integrated OpenAI GPT APIs with internal systems; developed predictive analytics models for churn, care gaps, and plan optimization. Collaborated with clinical teams to en

Machine Learning Engineer at Port Authority of NY/NJ

April 1, 2019 - August 1, 2020

Developed predictive maintenance and anomaly detection for IoT and operational telemetry; built time-series forecasts (ARIMA/LSTM), random forest, gradient boosting for degradation patterns, and proactive maintenance decisions. Supported AWS-based ML workflows with EC2, S3, and ECS; built streaming and batch inference pipelines with Kafka and Spark Streaming; created containerized services with Docker and Flask APIs for internal consumption; implemented NLP/text mining on technician notes using SpaCy; created dashboards in Power BI to surface maintenance risk indicators; integrated ML models with ticketing and monitoring systems; contributed to DevOps practices with CI/CD and versioning.

Data Scientist at Walmart

January 1, 2018 - March 1, 2019

Led ML pipelines on Azure Databricks for demand forecasting and inventory optimization; built models using Regression, Random Forest, XGBoost, and LSTM; improved stock stability and replenishment decisions. Established MLOps using MLflow, Azure Data Factory, Airflow; containerized models with AKS; built retrieval and search for product discovery; implemented price optimization models; real-time store analytics with Kafka; forecasting for utilities; connected ML predictions with ERP/MES/inventory platforms; produced leadership dashboards in Tableau and Google Data Studio; supported analytics modernization for scalable ingestion and distributed ML workloads.

Data Engineer at Aartisto Solutions

July 1, 2015 - June 1, 2017

Developed data integration pipelines for drone imagery, satellite feeds, and IoT sensor data into unified analytical datasets using Spark and Hadoop; built feature pipelines with soil metrics, regional climate patterns, and vegetation signals for ML workflows. Maintained on-prem Hadoop clusters; preprocessed agricultural imagery with OpenCV; stabilized ETL processes merging satellite imagery, IoT sensor outputs, and agronomic metadata; collaborated with agronomists to align data outputs with practical decision workflows. Supported predictive pipelines by preparing structured datasets for crop health identification and early YOLO-based detections; delivered Tableau dashboards for field planning and operational insights.

Senior AI Machine Learning Engineer at Centene Corporation

September 1, 2020 - December 1, 2022

Led development of a Generative AI virtual assistant using GPT-3 and RAG workflows with FAISS/Elasticsearch/Vertex AI embeddings to retrieve policy rules and clinical guidance. Advanced NLP/NLU pipelines (Transformers, spaCy) for entity extraction and sentiment analysis; supported clinical note summarization and authorization/explanation flows. Implemented multilingual and PHI-conscious generation, synthetic data strategies for sparse clinical scenarios, Vertex AI Pipelines/Model Registry, and HIPAA-aligned governance across production ML assets.

Python Developer at Aartisto Solutions

July 1, 2015 - June 1, 2017

Built data pipelines merging drone imagery, satellite feeds, and IoT sensor data using Spark/Hadoop; preprocessed imagery with OpenCV; developed feature-ready datasets for ML workflows; deployed on-prem Hadoop clusters; collaborated with agronomists to align outputs with practical decision workflows; documented data lineage and processing dependencies; supported scalable AWS-based inference workloads.

Senior AI / Machine Learning Engineer at Centene Corporation

September 1, 2020 - December 1, 2022

Joined Centene as a Senior AI / ML Engineer, leading AI-driven solutions focused on healthcare claims intelligence and member support automation. Built Conversational AI agents using Google Vertex AI and Dialogflow CX to support member and agent interactions, with HIPAA-compliant data handling. Implemented NLP/NLU capabilities including intent classification, slot filling, and context management for complex healthcare conversations. Developed retrieval-augmented QA workflows using FAISS and Elasticsearch to fetch coverage rules and policy clauses. Tuned embeddings and applied PEFT / prompt tuning to improve domain relevance while controlling cost. Built data/ML pipelines on Google Vertex AI, supporting batch training, model versioning, and controlled deployment. Exposed AI outputs via REST APIs and integrated with member portals, enabling human-in-the-loop reviews. Evaluated model quality with precision, recall, F1, and clinically aligned validation. Collaborated with clinical teams, c