I’m Guna Sekhar Mudduluru, a Generative AI Engineer with 3+ years of experience building enterprise-grade AI systems, including Large Language Model (LLM) applications and scalable cloud-native solutions. I focus on practical implementations of Retrieval-Augmented Generation (RAG), AI agents, and prompt engineering, turning complex data and business needs into reliable automation and decision support. In my recent work, I’ve designed governed analytics and secure enterprise assistants, and I’ve helped teams integrate AI into production workflows to improve efficiency and data operations. I also bring strong MLOps and Responsible AI practices to the table—deploying and maintaining machine learning models with robust pipelines, monitoring, and real-time inference services across healthcare and financial domains.

Guna Sekhar Mudduluru

I’m Guna Sekhar Mudduluru, a Generative AI Engineer with 3+ years of experience building enterprise-grade AI systems, including Large Language Model (LLM) applications and scalable cloud-native solutions. I focus on practical implementations of Retrieval-Augmented Generation (RAG), AI agents, and prompt engineering, turning complex data and business needs into reliable automation and decision support. In my recent work, I’ve designed governed analytics and secure enterprise assistants, and I’ve helped teams integrate AI into production workflows to improve efficiency and data operations. I also bring strong MLOps and Responsible AI practices to the table—deploying and maintaining machine learning models with robust pipelines, monitoring, and real-time inference services across healthcare and financial domains.

Available to hire

I’m Guna Sekhar Mudduluru, a Generative AI Engineer with 3+ years of experience building enterprise-grade AI systems, including Large Language Model (LLM) applications and scalable cloud-native solutions. I focus on practical implementations of Retrieval-Augmented Generation (RAG), AI agents, and prompt engineering, turning complex data and business needs into reliable automation and decision support.

In my recent work, I’ve designed governed analytics and secure enterprise assistants, and I’ve helped teams integrate AI into production workflows to improve efficiency and data operations. I also bring strong MLOps and Responsible AI practices to the table—deploying and maintaining machine learning models with robust pipelines, monitoring, and real-time inference services across healthcare and financial domains.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate
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Work Experience

Generative AI Engineer at Cisco
February 1, 2026 - Present
Built agentic AI solutions to automate engineering workflows such as code generation, test case creation, documentation, and developer assistance, improving engineering productivity. Designed and deployed an enterprise Retrieval-Augmented Generation (RAG) assistant to accelerate knowledge retrieval and streamline internal data operations. Implemented governed analytical datasets in Google Cloud BigQuery to support scalable enterprise analytics and regulatory compliance. Developed secure ThoughtSpot dashboards with row-level security for self-service analytics while maintaining data governance, and collaborated with cross-functional teams to integrate AI into production workflows and improve operational efficiency.
AI/ML Engineer Intern at UnitedHealth Group
May 1, 2025 - December 31, 2025
Improved patient risk prediction accuracy by 28% by developing and deploying AWS SageMaker machine learning models, contributing to reduced hospital readmissions. Reduced enterprise data latency by 40% through automated ETL pipelines using Python, SQL, Pandas, and AWS S3. Strengthened Responsible AI adoption with fairness monitoring frameworks and HIPAA-aligned ML practices. Increased workflow efficiency by 25% by deploying scalable FastAPI/Flask inference services for real-time clinical decision support. Built executive dashboards integrating predictive analytics and designed automated model retraining workflows to improve production reliability and long-term performance.
AI/ML Engineer at ACL Digital
June 1, 2021 - December 31, 2023
Reduced credit risk prediction errors by 22% using regression and classification models to enhance financial portfolio quality. Decreased manual review effort by 35% with TensorFlow and PyTorch deep learning models for NLP-driven document analysis. Achieved 99.5% production availability by implementing containerized Docker-based MLOps pipelines integrated with CI/CD automation. Integrated ML outputs into Power BI dashboards to provide real-time business intelligence. Automated model retraining and improved scalability and deployment overhead. Applied deep learning for enterprise text and image analytics to accelerate reporting and business insights.

Education

Master of Science, Information Technology at University of South Florida
January 11, 2030 - September 2, 2026
Bachelor of Science, Computer Science & Engineering at Velammal Institute of Technology
January 11, 2030 - September 2, 2026

Qualifications

AWS Certified AI Practitioner
January 11, 2030 - September 2, 2026
Microsoft Azure AI Engineer Associate (AI-102)
January 11, 2030 - September 2, 2026

Industry Experience

Healthcare, Financial Services, Computers & Electronics, Professional Services