I am Bhavya Vankayalapati, a Senior Data Scientist and Generative AI/ML Engineer with 9+ years of experience delivering production-grade ML and LLM-driven systems across financial services, healthcare, telecommunications, and aviation. I design and deploy enterprise Gen AI platforms (Azure OpenAI, AWS Bedrock) with Retrieval-Augmented Generation, hybrid semantic search, structured outputs, and deterministic orchestration, while building end-to-end ML pipelines from data ingestion to monitoring and retraining. My work has consistently driven measurable business impact, from faster onboarding and improved forecasting to reduced latency and enhanced fraud detection. I thrive in multi-cloud, governance-aware environments, delivering scalable, explainable AI with robust MLOps, drift monitoring, and auditable workflows. I enjoy collaborating with cross-functional teams to translate complex data into strategic decisions, and I continuously optimize for security, cost efficiency, and regulatory compliance.

Bhavya Vankayalapati

I am Bhavya Vankayalapati, a Senior Data Scientist and Generative AI/ML Engineer with 9+ years of experience delivering production-grade ML and LLM-driven systems across financial services, healthcare, telecommunications, and aviation. I design and deploy enterprise Gen AI platforms (Azure OpenAI, AWS Bedrock) with Retrieval-Augmented Generation, hybrid semantic search, structured outputs, and deterministic orchestration, while building end-to-end ML pipelines from data ingestion to monitoring and retraining. My work has consistently driven measurable business impact, from faster onboarding and improved forecasting to reduced latency and enhanced fraud detection. I thrive in multi-cloud, governance-aware environments, delivering scalable, explainable AI with robust MLOps, drift monitoring, and auditable workflows. I enjoy collaborating with cross-functional teams to translate complex data into strategic decisions, and I continuously optimize for security, cost efficiency, and regulatory compliance.

Available to hire

I am Bhavya Vankayalapati, a Senior Data Scientist and Generative AI/ML Engineer with 9+ years of experience delivering production-grade ML and LLM-driven systems across financial services, healthcare, telecommunications, and aviation. I design and deploy enterprise Gen AI platforms (Azure OpenAI, AWS Bedrock) with Retrieval-Augmented Generation, hybrid semantic search, structured outputs, and deterministic orchestration, while building end-to-end ML pipelines from data ingestion to monitoring and retraining. My work has consistently driven measurable business impact, from faster onboarding and improved forecasting to reduced latency and enhanced fraud detection.

I thrive in multi-cloud, governance-aware environments, delivering scalable, explainable AI with robust MLOps, drift monitoring, and auditable workflows. I enjoy collaborating with cross-functional teams to translate complex data into strategic decisions, and I continuously optimize for security, cost efficiency, and regulatory compliance.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
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Work Experience

Gen AI Engineer at Mastercard
June 1, 2024 - Present
Designed and deployed a governed, multi-model Agentic RAG platform automating merchant onboarding, sandbox validation, and integration intelligence across global regions. Re-architected onboarding workflows with an agent-style GenAI platform, built ingestion pipelines for 2,000+ pages of API documentation, and implemented a deterministic, multi-agent LangGraph orchestration with MCP. Developed a Verification Agent, rule-based confidence scoring, and an LLM-as-a-Judge harness with MLflow. Established automated regression tests, semantic caching, and prompt compression, enabling multi-model routing across Azure OpenAI and AWS Bedrock. Containerized services with Docker on AKS, used Terraform for multi-region deployments, and integrated Credo AI Registry and Azure Content Safety for governance and PII handling. Result: 60% onboarding time reduction across 12 regions.
AI/ML Engineer at United Health Group
July 1, 2022 - May 1, 2024
Engineered and scaled a multi-cloud AI platform for high-volume pharmacy operations (5M+ pill-validations monthly with 99.9% accuracy). Built PySpark ETL on AWS Glue, integrating real-time events from Snowflake and Kafka into a centralized feature layer. Implemented schema validation, PHI-safe processing, and leakage-aware features; created a centralized feature store for training-serving parity. Trained forecasting models in SageMaker and analyzed SDoH data with Vertex AI. Implemented an Agentic RAG pipeline for semantic search of medication interaction docs and migrated workloads to serverless architectures (Lambda/SQS). Established MLflow-based experiment tracking, drift monitoring, CI/CD, and HIPAA-compliant data handling across 300+ locations.
AI Engineer / SR Data Scientist at AT & T
January 1, 2020 - June 1, 2022
Built production-grade predictive maintenance and security automation for national 5G infrastructure. Designed large-scale telemetry ingestion via Azure Data Factory (ADFX) and ADLS Gen2, engineered PySpark-based feature transformations, and trained XGBoost/LightGBM models with forward-looking validation. Implemented scheduled retraining, SHAP/LIME interpretability, and an Agentic RAG workflow using Azure OpenAI and LangChain. Migrated legacy workloads to serverless (Azure Functions, SQS) and established CI/CD with GitHub Actions/Azure DevOps, MLflow tracking, and drift monitoring. Implemented RBAC, encryption, and audit logging with Prometheus and Splunk monitoring.
Data Scientist at American Airlines
October 1, 2018 - December 1, 2019
Developed predictive gate allocation models using XGBoost and Random Forest to optimize gate assignment, considering aircraft type, delays, and constraints. Reduced gate planning cycle time from ~4 hours to under 3 minutes and improved taxi-in routing via data-driven optimization. Built SQL-based data pipelines consolidating flight, maintenance, and weather data; deployed batch scoring with SHAP-based explanations for leadership. Delivered Power BI dashboards to support operations decisions, contributing to on-time performance improvements and revenue optimization.
Python Developer at Edvensoft Solutions India Pvt. Ltd
August 1, 2016 - June 1, 2018
Developed backend modules in Python/Flask with RESTful APIs linking Oracle and PostgreSQL systems. Implemented ETL-style transformations to migrate and standardize heterogeneous data; automated synchronization with Linux cron. Optimized SQL queries, improved reporting latency, and ensured data integrity with audit logging. Implemented unit/integration testing, Git versioning, Agile practices, and deployed containerized services with CI/CD pipelines.

Education

Bachelor of Technology in Computer Science at Malineni Perumallu Engineering College (Affiliated to JNTUK)
January 11, 2030 - February 18, 2026

Qualifications

Add your qualifications or awards here.

Industry Experience

Financial Services, Healthcare, Telecommunications, Transportation & Logistics, Travel & Hospitality