Aug 2024 – Dec 2024 · 4 mos · Bengaluru, Karnataka, India · Hybrid

• Designed, implemented, and deployed 15+ full-stack features for a large-scale in-house Java enterprise application, utilizing
• technologies including JDBC for efficient data access, EJB for scalable business logic, and Primefaces for UI;delivering
• seamless backend and front-end integration for thousands of daily users
• Delivered development tasks 20–30% before JIRA sprint deadlines by prioritizing critical requirements, revamping sprint
• planning, and driving Agile ceremonies; accelerated release cycles, boosting team throughput by 25%
• Adapted to and enhanced a 17-year legacy codebase, rapidly mastering complex application logic and launching new features
• while safeguarding all existing functionalities; preserved 100% application integrity and enabled seamless feature rollouts
• Employed rigorous unit testing with JUnit, resulting in a notable reduction of post-release defects and facilitating smooth
• transitions for feature enhancements during QA cycles

Aug 2023 – Jul 2024 · 11 mos · Bengaluru, Karnataka, India · Hybrid

• Spearheaded development and integration of Generative AI-powered features using GPT-4o, Ada API and Django, driving
• major enhancements in intelligent automation across core applications
• Architected and automated help file generation within in-house platforms by leveraging GPT-4o LLM and Ada API, increasing
• help file PDF engagement by 30% and streamlining support workflows
• Formulated and executed optimized model delivery pipelines and codebase, resulting in an 18% increase in processing
• efficiency through targeted refactoring and performance tuning
• Engineered user-centric features such as image querying and voice input to augment application support capabilities and
• improve user experience

Feb 2023 – Apr 2023 · 2 mos · Bengaluru, Karnataka, India · On-site

• Designed and implemented an end-to-end ML pipeline; developed a custom ensemble of Random Forest and deep learning
• models for image and sound data from 800+ clinical patients, elevating multiclass classification accuracy from 55% to 75%
• Built data extraction pipelines for large-scale healthcare datasets, including advanced feature extraction from image data using
• Variational Autoencoders (VAEs) to learn meaningful latent representations
• Led dataset engineering, model architecture design, and system optimization for a comprehensive healthcare AI platform
• Performed visualization, data extraction, and trend analysis on a US healthcare dataset of 1.2 billion patient records; automated
• data workflows to reduce manual intervention by 30%
• Drove advanced data mining and extraction initiatives on large-scale clinical datasets; created and validated supervised learning
• models to predict stroke risk, enabling intervention and data-driven patient care

Jun 2022 – Jul 2022 · 1 mo · Bengaluru, Karnataka, India

• Collaborated on Zmanda’s Django-driven enterprise backup platform by fortifying backend data protection, streamlining
• API-driven operations, and amplifying documentation; contributed to adoption across 45+ countries and empowered secure,
• compliant data management for leading clients
• Executed three high-impact backend deliverables assigned by team leads, applying advanced Django REST Framework
• expertise, architecting scalable APIs, and resolving complex endpoint issues with diagnostic tools such as Postman
• Documented and mapped over 250+ endpoints in the application, providing detailed traceability across backend services and
• improving overall maintainability and onboarding for new team members
• Improved backend efficiency by identifying and resolving workflow bottlenecks during endpoint analysis, leading to smoother
• feature implementation and accelerated development cycles across the team