Looks like you have JavaScript disabled. For the full Twine experience, you will need to re-enable it.

AI and ML Engineer and Data Scientist with 9+ years of experience solving business problems in healthcare, financial services, public sector, and retail using Python, Generative AI, and Agentic AI to build practical AI systems from real operational needs. Primary hands-on focus includes LangChain/LangGraph, RAG, and MCP integrations for document intelligence and workflow automation, plus experience delivering ML models for credit risk, fraud detection, document classification, forecasting, dynamic pricing, and recommendations with strong MLOps/LLMOps practices.…AI and ML Engineer and Data Scientist with 9+ years of experience solving business problems in healthcare, financial services, public sector, and retail using Python, Generative AI, and Agentic AI to build practical AI systems from real operational needs. Primary hands-on focus includes LangChain/LangGraph, RAG, and MCP integrations for document intelligence and workflow automation, plus experience delivering ML models for credit risk, fraud detection, document classification, forecasting, dynamic pricing, and recommendations with strong MLOps/LLMOps practices.

Vijender Reddy Kooturu

AI Engineer, Data Scientist, Web Developer, +2





AI and ML Engineer and Data Scientist with 9+ years of experience solving business problems in healthcare, financial services, public sector, and retail using Python, Generative AI, and Agentic AI to build practical AI systems from real operational needs. Primary hands-on focus includes LangChain/LangGraph, RAG, and MCP integrations for document intelligence and workflow automation, plus experience delivering ML models for credit risk, fraud detection, document classification, forecasting, dynamic pricing, and recommendations with strong MLOps/LLMOps practices.…AI and ML Engineer and Data Scientist with 9+ years of experience solving business problems in healthcare, financial services, public sector, and retail using Python, Generative AI, and Agentic AI to build practical AI systems from real operational needs. Primary hands-on focus includes LangChain/LangGraph, RAG, and MCP integrations for document intelligence and workflow automation, plus experience delivering ML models for credit risk, fraud detection, document classification, forecasting, dynamic pricing, and recommendations with strong MLOps/LLMOps practices.

Available to hire

AI and ML Engineer and Data Scientist with 9+ years of experience solving business problems in healthcare, financial services, public sector, and retail using Python, Generative AI, and Agentic AI to build practical AI systems from real operational needs.

Primary hands-on focus includes LangChain/LangGraph, RAG, and MCP integrations for document intelligence and workflow automation, plus experience delivering ML models for credit risk, fraud detection, document classification, forecasting, dynamic pricing, and recommendations with strong MLOps/LLMOps practices.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Language

English

Intermediate

Work Experience

Generative AI Engineer at CVS Health

March 1, 2025 - Present

Built healthcare Generative AI and Agentic AI solutions for pharmacy document intelligence using LangChain, LangGraph, LangGraph Studio, Vertex AI, and Pinecone. Developed agentic workflows for multi-step pharmacy document review with tool calling, agent memory, and structured outputs. Implemented MCP servers/clients to standardize reusable tool access to internal APIs for healthcare agents. Delivered production RAG pipelines including ingestion, chunking, embeddings, semantic retrieval, metadata filtering, and grounded answering from internal content. Exposed AI capabilities via FastAPI/REST services, deployed on GCP using Cloud Run, GKE, and Kubernetes, and added observability through LangSmith/Langfuse and Cloud Monitoring. Applied responsible AI practices (PII handling, access controls, audit logging, explainability review, and HIPAA-aware governance) and implemented MLflow-based LLMOps/MLOps with model and prompt versioning and CI/CD via GitHub Actions for reliable releases.

Data Scientist / AI-ML Engineer at Morgan Stanley

February 1, 2023 - February 28, 2025

Designed and developed ML solutions for credit risk, fraud detection, customer segmentation, and transaction anomaly detection using Azure Machine Learning and standard ML/DL models (scikit-learn, XGBoost, TensorFlow, PyTorch). Built financial document processing workflows using NLP for classification, entity extraction, summarization, and semantic search to make reports searchable and analyzable. Implemented retrieval workflows using Azure OpenAI embeddings and metadata filtering for institutional knowledge access. Deployed and supported scoring services with Docker, Kubernetes, and Azure Kubernetes Service using REST APIs and monitored via Azure Monitor and Application Insights. Established governed model lifecycle practices with MLflow/Azure ML, Docker/Kubernetes, and CI/CD, and contributed to cross-functional alignment with risk/compliance stakeholders on AI governance and audit expectations.

Data Scientist / ML Engineer at State of Washington

June 1, 2020 - January 31, 2023

Developed citizen services reporting and document classification solutions using Python, scikit-learn, PySpark, and AWS SageMaker. Performed data discovery, profiling, cleaning, and transformation across structured and unstructured sources to support analysis and modeling. Built predictive models for demand and outcomes and created classification/segmentation models to support operational resource allocation. Implemented NLP preprocessing (TF-IDF, Word2Vec) and text classification for routing incoming case documents into appropriate workflows. Designed distributed ML and ETL pipelines using PySpark, Spark MLlib, S3, Lambda, DynamoDB, and automated CI/CD with CodePipeline/CodeBuild. Delivered stakeholder-facing Tableau dashboards and established monitoring, drift review, and retraining workflows using CloudWatch to maintain production reliability.

Python Developer at Virtusa

September 1, 2016 - November 30, 2017

Developed Python/Django backend services and REST APIs supporting web applications, with MongoDB-backed data models and modular service layers for centralized validation and business rules. Integrated frontend experiences with React/JavaScript by building RESTful endpoints, handling payloads, and ensuring robust error handling. Improved performance through MongoDB query tuning and indexing. Supported stable release cycles with unit/integration testing, Git-based collaboration, and CI/CD practices, assisting deployment and monitoring of Python applications in AWS-backed environments as part of Agile delivery.