Santosh Gurugubelli

Designed and implemented intelligent application features by integrating Large Language Model (LLM) APIs into scalable web and mobile platforms, enhancing personalized user experiences and enabling real-time decision-making.

Built scalable and high-performance web applications using React.js, following modular UI architecture principles for enterprise platforms and extended capabilities to mobile environments, ensuring seamless cross-platform user experiences. Leveraged Python-based backend services to orchestrate LLM interactions, enabling dynamic content generation, conversational interfaces, and intelligent automation.

Utilized Google Cloud Run to deploy scalable, high-concurrency services supporting real-time UI interactions and AI-driven workflows, containerized backend services that handle LLM orchestration, API integrations, and event-driven processing, ensuring high availability and low-latency responses for AI-powered features.

Collaborated with cross-functional teams to integrate LLM-driven capabilities into production systems, aligning frontend (React.js) and backend (Python microservices) components to deliver cohesive, AI-enhanced user journeys across web and mobile applications.

Architected and deployed agentic workflows using modular service design with MCP (Model Context Protocol) servers and multi-step reasoning pipelines, facilitating autonomous task execution and improving contextual understanding across applications. Contributed to defining reusable UI patterns and component structures to ensure consistency and scalability across applications.

• Developed an AI-powered shopping mobile and web application that enables users to identify products from images, videos, or real-time camera input and instantly receive purchase links from e-commerce platforms such as Amazon and Flipkart.
• Integrated AWS Rekognition with custom-trained models to enhance object detection capabilities, improving robustness across diverse visual inputs.
• Designed and implemented end-to-end computer vision pipelines using YOLOv3 with custom-labeled datasets to detect and classify products from screen captures, live camera feeds, and uploaded media with high accuracy.
• Built and deployed Python-based RESTful services to serve machine learning models, enabling real-time inference and seamless integration with frontend applications across mobile (React Native) and web (React.js).
• Implemented predictive analytics models for customer segmentation, lifetime value estimation, and churn detection, enabling targeted recommendations and improving customer retention strategies.
• Leveraged Oracle Analytics Cloud (OAC) in combination with machine learning models to generate actionable business insights, including customer behavior analysis, sales trend forecasting, retention tracking, and churn prediction.
• Developed data pipelines using Python (Pandas, NumPy, Matplotlib, scikit-learn) to preprocess large datasets, train predictive models, and feed analytical results into OAC dashboards for business intelligence and decision-making.
• Engineered a unique feature allowing users to capture screenshots from videos or mobile screens, automatically detect visible products, and generate contextual shopping recommendations with affiliated purchase links.
• Built scalable, responsive user interfaces using React.js and React Native, ensuring a seamless cross-platform experience across Android, iOS, and web environments.
• Supported enterprise application architecture by ensuring seamless integration between frontend systems and backend domain models.

• Developed and customized solutions in Oracle E-Business Suite R12 using PL/SQL, SQL, and Oracle Forms, enhancing functionality of core business modules including AP, AR, GL, PO, and INV.
• Designed and implemented Concurrent Programs, including PL/SQL-based, Host, and SQL*Loader programs for data processing, validation, and automation of business workflows.
• Built and customized reports using Oracle Reports (RDF) and BI Publisher (XML Publisher), including creation of XML templates, data templates, and bursting solutions for dynamic report generation.
• Developed inbound and outbound interfaces using Oracle Open Interface tables, standard APIs, and custom PL/SQL packages to integrate Oracle Apps with external systems.
• Worked extensively on data migration and conversion using SQL*Loader, external tables, and custom scripts, ensuring data integrity and validation across environments.
• Performed performance tuning of complex SQL queries and PL/SQL procedures using explain plans, indexing strategies, and query optimization techniques, resulting in improved system efficiency.
• Worked with Multi-Org (MOAC) architecture and handled security setups, responsibilities, and profile options to ensure proper data access control.
• Debugged and resolved production issues by analyzing logs, trace files, and concurrent request outputs, ensuring minimal downtime and system stability.
• Followed Oracle AIM/implementation methodologies and maintained proper documentation for technical design, development, and deployment processes.

• Architected robust data integration layers leveraging Oracle APIs, interface tables, and SQL*Loader to enable seamless communication between Oracle EBS and external enterprise systems.
• Engineered scalable customizations within Oracle Apps R12 by developing high-performance PL/SQL components and modular data integration pipelines, enhancing system responsiveness and user experience.
• Optimized enterprise workloads by tuning SQL/PLSQL code, reducing execution time of critical concurrent programs, and improving overall application throughput.
• Automated complex business processes using Oracle Workflow, Alerts, and backend scripting, minimizing manual intervention and improving operational efficiency.
• Delivered enterprise-grade reporting solutions using BI Publisher with dynamic templates and automated distribution mechanisms, streamlining report generation and accessibility for stakeholders.

• Integrated Oracle APEX with Oracle Apps R12 database schemas using optimized SQL queries, views, and PL/SQL packages to fetch and process live transactional data.
• Developed custom data models and REST-enabled services to expose Oracle EBS data securely for consumption within APEX applications.
• Implemented role-based access control (RBAC) and session management in APEX to ensure secure and personalized access to project and transaction-level insights.
• Optimized performance of APEX pages and backend queries by implementing indexing strategies, query tuning, and efficient PL/SQL logic.
• Built interactive dashboards and reports in APEX to monitor current transactions across modules (AP, AR, PO, GL, INV), enabling stakeholders to track financial and operational status in a centralized interface.
• Collaborated with business and functional teams to translate reporting requirements into scalable APEX solutions that align with Oracle Apps R12 architecture.
• Designed and developed a dynamic web-based project status tracking application using Oracle APEX, providing real-time visibility into transactional data from Oracle E-Business Suite R12.