Hi, my name is
Srinivasa Reddy Kommireddy.
I build AI systems and data pipelines.
Generative AI Engineer & Data Engineer with 4+ years building production Generative AI systems and real-time pipelines for healthcare and insurance — using Python, SQL, Snowflake, Databricks, and Azure OpenAI.
View My Work Download Resume (PDF)About Me
I'm a Generative AI Engineer and Data Engineer with 4+ years of experience building real-time data pipelines and production AI systems across healthcare and financial claims platforms. At UnitedHealth Group, I build denial-explanation assistants and retrieval-augmented generation (RAG) systems that help analysts understand claims and coding policies.
My work spans 50M+ claims and $150M+ in healthcare spend, with $4.2M in reimbursement recovery opportunities identified and a 15% reduction in avoidable denials. I build governed pipelines, feature datasets, and analytics that support Finance, Operations, and data science teams.
Microsoft Certified: Fabric Analytics Engineer Associate and Power BI Data Analyst Associate.
Technologies and practices I work with:
- OpenAI API & Azure OpenAI
- RAG & Semantic Search
- Prompt Engineering & LLM Evaluation
- Python, Pandas & Scikit-learn
- SQL & Data Modeling
- Databricks & PySpark
- Spark Structured Streaming
- Snowflake & ETL/ELT
- Airflow & CDC Pipelines
- Azure & AWS
- Power BI, DAX & RLS
- Data Quality & Feature Engineering
Where I've Worked
Generative AI Engineer & Data Engineer @ UnitedHealth Group
Feb 2025 – Present
- Engineered an OpenAI API and Python denial-explanation pipeline that generates plain-language explanations of claim-denial propensity model outputs in near real time, reducing manual case-review time.
- Built a RAG-based coding and policy knowledge engine with Azure OpenAI, vector embeddings, and semantic search over CMS guidelines and payer policies, enabling natural-language retrieval of ICD-10/CPT rules.
- Built real-time and batch pipelines in Azure Databricks (PySpark) processing 50M+ claims and $150M+ in healthcare spend, powering Medical Loss Ratio and AR-aging reporting.
- Designed SQL-driven ETL/ELT pipelines to investigate coding and authorization gaps, reducing avoidable denials by 15% and driving an estimated $4.2M increase in annual reimbursement recovery.
- Built feature-engineering pipelines with Python, pandas, scikit-learn, and PySpark for claim-denial propensity modeling, and evaluated AI-generated explanations against clinical and coding accuracy standards.
- Standardized EDI 837/835 and FHIR datasets through HIPAA-compliant pipelines with automated checks achieving 99.9% data integrity. Statistical validation confirmed a $2M reduction in manual rework costs.
- Engineered Snowflake models and pipelines for Power BI dashboards and partnered with Finance and Operations to improve authorization workflows, reducing processing delays by 22%.
Data Engineer @ Swiss Re
Jun 2020 – Jul 2023
- Architected a real-time claims analytics model in Databricks using SQL and PySpark to centralize policy terms, trigger attributes, and claims data for pre-approval validation and operational reporting.
- Explored early OpenAI API and prompt-engineering applications to prototype natural-language summaries of claims-triage rationale and policy exceptions.
- Engineered rule-based pipelines and exception reporting with SQL, PySpark, and DAX, enabling 25–35% safe auto-approval and reducing median claims triage time by 87%, from 24 hours to 3 hours.
- Automated data-quality and reconciliation checks for schema consistency, nulls, ranges, and cross-field business rules, reducing manual validation effort by 50% and reconciliation exceptions by 40%.
- Built the semantic data layer and row-level-security model behind Power BI dashboards monitoring claims SLAs, auto-approval performance, and exception drivers.
- Partnered with Actuaries and Claims Leads to translate policy language and risk thresholds into governed SQL and PySpark business rules, maintaining controlled updates and consistent reporting.
Education
St. Francis College
Master of Science in Information Technology
Aug 2023 – Dec 2024
Certifications
Microsoft Certified: Fabric Analytics Engineer Associate
Microsoft Certified: Power BI Data Analyst Associate
Some Things I've Built
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RetailPulse - Fabric Analytics
Enterprise-grade Microsoft Fabric analytics platform demonstrating a full Lakehouse architecture. Features raw-to-silver-to-gold processing, Warehouse Star Schema, and real-time Power BI reporting.
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Hospital Analytics Platform
End-to-end data engineering solution ingesting data from 3 separate hospital systems into Snowflake. Orchestrated via Mage.ai with dbt transformations and data quality checks.
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Flipkart Sentiment Analysis
NLP machine learning pipeline classifying product reviews as positive or negative. Features a dual-analysis approach (VADER + Logistic Regression) interacting via a Streamlit web app.
Resume
Explore my experience in Generative AI, data engineering, and claims analytics, including my technical skills, education, and Microsoft certifications.
Download Resume (PDF)What's Next?
Get In Touch
I'm open to Generative AI and data engineering opportunities. Get in touch to discuss production AI systems, real-time data pipelines, or claims analytics.
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