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Hi, I’m Sai Charitha Konda, a Senior AI/ML Engineer with 11+ years of experience designing scalable machine learning, deep learning, and generative AI systems across logistics, finance, healthcare, and industrial sectors. I specialize in enterprise-grade GenAI platforms leveraging GPT-4, Llama 3, and Azure OpenAI to deliver production-ready copilots and knowledge-driven assistants. I’ve built robust RAG pipelines, integrated vector databases, and implemented grounding-conscious retrieval strategies to support contextual reasoning in complex environments. I enjoy turning data into practical AI solutions that scale in production, collaborating with cross-functional teams in Agile settings, and upholding Responsible AI principles. My work spans secure API design, containerized deployments on Kubernetes, and end-to-end workflows from data ingestion to model governance and monitoring, with a focus on reliability and regulatory compliance across industries.…Hi, I’m Sai Charitha Konda, a Senior AI/ML Engineer with 11+ years of experience designing scalable machine learning, deep learning, and generative AI systems across logistics, finance, healthcare, and industrial sectors. I specialize in enterprise-grade GenAI platforms leveraging GPT-4, Llama 3, and Azure OpenAI to deliver production-ready copilots and knowledge-driven assistants. I’ve built robust RAG pipelines, integrated vector databases, and implemented grounding-conscious retrieval strategies to support contextual reasoning in complex environments. I enjoy turning data into practical AI solutions that scale in production, collaborating with cross-functional teams in Agile settings, and upholding Responsible AI principles. My work spans secure API design, containerized deployments on Kubernetes, and end-to-end workflows from data ingestion to model governance and monitoring, with a focus on reliability and regulatory compliance across industries.

Sai Charitha Konda

Data Scientist, AI Engineer, AI Developer, +3

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Hi, I’m Sai Charitha Konda, a Senior AI/ML Engineer with 11+ years of experience designing scalable machine learning, deep learning, and generative AI systems across logistics, finance, healthcare, and industrial sectors. I specialize in enterprise-grade GenAI platforms leveraging GPT-4, Llama 3, and Azure OpenAI to deliver production-ready copilots and knowledge-driven assistants. I’ve built robust RAG pipelines, integrated vector databases, and implemented grounding-conscious retrieval strategies to support contextual reasoning in complex environments. I enjoy turning data into practical AI solutions that scale in production, collaborating with cross-functional teams in Agile settings, and upholding Responsible AI principles. My work spans secure API design, containerized deployments on Kubernetes, and end-to-end workflows from data ingestion to model governance and monitoring, with a focus on reliability and regulatory compliance across industries.…Hi, I’m Sai Charitha Konda, a Senior AI/ML Engineer with 11+ years of experience designing scalable machine learning, deep learning, and generative AI systems across logistics, finance, healthcare, and industrial sectors. I specialize in enterprise-grade GenAI platforms leveraging GPT-4, Llama 3, and Azure OpenAI to deliver production-ready copilots and knowledge-driven assistants. I’ve built robust RAG pipelines, integrated vector databases, and implemented grounding-conscious retrieval strategies to support contextual reasoning in complex environments. I enjoy turning data into practical AI solutions that scale in production, collaborating with cross-functional teams in Agile settings, and upholding Responsible AI principles. My work spans secure API design, containerized deployments on Kubernetes, and end-to-end workflows from data ingestion to model governance and monitoring, with a focus on reliability and regulatory compliance across industries.

Available to hire

Hi, I’m Sai Charitha Konda, a Senior AI/ML Engineer with 11+ years of experience designing scalable machine learning, deep learning, and generative AI systems across logistics, finance, healthcare, and industrial sectors. I specialize in enterprise-grade GenAI platforms leveraging GPT-4, Llama 3, and Azure OpenAI to deliver production-ready copilots and knowledge-driven assistants. I’ve built robust RAG pipelines, integrated vector databases, and implemented grounding-conscious retrieval strategies to support contextual reasoning in complex environments.

I enjoy turning data into practical AI solutions that scale in production, collaborating with cross-functional teams in Agile settings, and upholding Responsible AI principles. My work spans secure API design, containerized deployments on Kubernetes, and end-to-end workflows from data ingestion to model governance and monitoring, with a focus on reliability and regulatory compliance across industries.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

Senior AI/ML Engineer at AVEVA

January 1, 2024 - Present

Delivered enterprise GenAI solutions using Python, AWS, and LLM-based architectures; built a hybrid AI architecture integrating on-prem SQL Server, cloud services, and microservice-based LLM inference pipelines to support scalable GenAI workloads. Built ingestion pipelines sourcing data from SQL Server, REST APIs, and batch files; developed data transformation workflows using PySpark, Pandas, and AWS Glue; implemented vector storage with Pinecone, FAISS, and Elasticsearch; integrated LLMs (GPT-4, GPT-3.5, Llama 3.1); implemented RAG pipelines with LangChain and LlamaIndex; enhanced retrieval with hybrid search and reranking; performed prompt engineering; containerized inference with Docker; deployed scalable inference with AWS Lambda; automated CI/CD with Git and Azure DevOps; provisioning with CloudFormation/CDK; LLM Ops monitoring with CloudWatch and Datadog.

Python AI/ML Engineer at LA Care / Los Angeles County, CA

October 1, 2022 - December 1, 2023

Delivered healthcare-focused AI/ML solutions; built secure Azure-based AI architecture; ingestion pipelines via Azure Data Factory; data processing with PySpark and Pandas; managed data storage in Azure SQL and Snowflake; implemented data quality validation with Great Expectations; trained models for claims, utilization, and risk; exposed inference services via FastAPI; containerized with Docker and AKS; automated ML build and release with Git and Azure DevOps; API security with OAuth2/JWT; monitored models with Azure ML monitoring.

Python Developer- ML at Express Script

February 1, 2020 - September 1, 2022

Built enterprise-scale Python ML solutions for insurance risk modeling and cost optimization; batch data ingestion from Oracle, SQL Server, and flat files; data transformation with Pandas/NumPy/SQL; developed ML models using Scikit-Learn, XGBoost, and deep learning with TensorFlow/PyTorch; created reusable components; containerized workloads; integrated via Python APIs; automated build and deployment with Git/Jenkins; implemented scheduled scoring.

Data Analyst at ADP

September 1, 2014 - March 1, 2017

Delivered HR and payroll analytics; worked with Oracle databases; wrote complex SQL for reporting; data cleansing, reconciliation, and transformation; implemented data quality checks; supported dashboards and reporting for payroll and compliance; automated recurring reports; ensured auditability.

Data Scientist at UPS

June 1, 2017 - December 1, 2019

Delivered data science and analytics for shipment operations; extracted and analyzed large-scale shipment data with SQL and Python; performed data cleansing, aggregation, and transformation; supported Hadoop and Spark-based analytics; developed predictive models for delivery times and route efficiency; built dashboards and automated analytics workflows.

Senior AI/ML Engineer at LA Care

October 1, 2022 - December 1, 2023

Delivered healthcare-focused AI/ML solutions using Python on Azure, enabling compliant analytics and predictive insights across claims, utilization, and operational datasets. Built a secure cloud-first architecture with Azure SQL, Azure Data Factory, and Azure ML to support scalable model training and inference. Created ingestion pipelines from SQL Server, healthcare APIs, and batch files using Azure Data Factory connectors. Processed data with PySpark and Pandas; managed curated stores in Azure SQL and Snowflake for ML workflows. Implemented Great Expectations data quality checks; developed predictive models (Scikit-learn, XGBoost, LightGBM) for claims scoring and risk modeling with engineered temporal features. Built NLP pipelines with spaCy and BERT embeddings for unstructured notes; explored embedding-based and LLM-assisted approaches for future automation. Exposed real-time inference via FastAPI; containerized on AKS; automated CI/CD with Git and Azure DevOps; API security via OAu

Data Scientist at Express Scripts

February 1, 2020 - September 1, 2022

Delivered data science and analytics solutions using Python and Azure for claims, utilization, and operational datasets. Built ingestion and processing pipelines from SQL Server, healthcare APIs, and batch files with Azure Data Factory. Processed data with PySpark and Pandas; curated datasets in Azure SQL and Snowflake for ML training and inference. Developed predictive models (Scikit-learn, XGBoost) for claims forecasting and utilization analysis; engineered temporal features; performed time-series analysis for capacity planning. Implemented NLP on clinical notes with spaCy and embeddings; evaluated embedding-based and LLM-assisted approaches for automation. Exposed ML inference via FastAPI; containerized with Docker; deployed on AKS; automated CI/CD with Git and Azure DevOps; API security via OAuth2/JWT. Monitored model performance and drift with Azure ML; documented with Swagger/OpenAPI and Confluence.

Python AI/ML Engineer at LA Care

October 1, 2022 - December 1, 2023

Developed predictive healthcare intelligence using Python, Scikit-Learn, XGBoost, and PyTorch for risk adjustment modeling and high-cost member identification. Built scalable analytics on AWS (S3, Redshift) and Apache Spark (PySpark) to process Medicaid claims and eligibility data. Collaborated with actuarial and clinical stakeholders to align models with Medicaid quality measures and compliance. Built secure ingestion pipelines with AWS Glue, Airflow, and PySpark; processed HL7 v2, ICD-10, and CPT codes; optimized storage/query with S3/Redshift/Athena. Applied FAISS embeddings for semantic indexing of clinical/policy documents; used ClinicalBERT/BioBERT for domain NLP; built risk stratification and utilization models with TensorFlow/XGBoost. Implemented lightweight RAG using OpenAI API and LangChain for policy guidance retrieval; tracked experiments with MLflow; explained models with SHAP/LIME for governance; ensured HIPAA compliance; deployed FastAPI-based inferences on EKS; automate

Python Developer - ML at Express Script

February 1, 2020 - September 1, 2022

Developed predictive analytics using Python, Scikit-Learn, and XGBoost to support pharmacy claims cost forecasting and fraud risk detection. Designed ETL pipelines using SQL Server, T-SQL, and Azure Data Lake; collaborated with actuarial and business teams to translate cost-containment strategies into ML use cases and deployment plans. Built distributed data transformations with PySpark on Databricks; standardized HL7 v2, ICD-10, and CPT codes; optimized relational storage and query performance in SQL Server/Azure SQL Database. Implemented model explainability with SHAP, deployed REST inferences via FastAPI/Flask on Azure App Service, and managed experiments with MLflow; automated CI/CD with Azure DevOps; implemented RBAC and encryption for PHI data; built operational dashboards with Power BI.