Software Engineer Computer Science

Jahnavi Bellapukonda

*********************@*****.*** +1-806-***-**** USA LinkedIn

Education

Master of Science, Texas Tech University 08/2023 - 05/2025 Lubbock, USA Computer Science

Bachelor of Technology, JNTU 06/2018 - 06/2022 Kakinada, India Computer Science and Engineering

Technical Skills

• Programming Languages & Scripting: Java (Microservices, Spring Boot, JDBC, OOP) Python (OOP, multithreading, exception handling), JavaScript (ES6+), Bash, SQL (advanced querying, joins, indexing), C, C++, R

• Frameworks & Libraries: Django, Flask, FastAPI, React.js, Redux, Bootstrap, HTML5, CSS3, AJAX, Jinja2, SQLAlchemy

• Databases & Data Storage: PostgreSQL, MySQL, MongoDB, Redis, SQLite, Azure SQL Database, Data Modeling

• Cloud, DevOps & CI/CD: AWS (EC2, S3, RDS, Lambda, CloudWatch, IAM), Azure (App Services, Blob Storage), Docker, Docker Compose, Jenkins, GitHub Actions, Azure DevOps, Maven, Poetry, Shell scripting

• Development Tools & Best Practices: Git, GitHub, GitLab, Bitbucket, Postman, Swagger/OpenAPI, PyTest, unittest, Selenium, JIRA, Confluence, Agile (Scrum/Kanban), CI/CD pipelines, TDD, Clean Architecture, SOLID principles, Linux Professional Experience

Software Engineer, Adobe 08/2024 – Present Remote, USA

• Built and scaled responsive, feature-rich web applications using Angular, HTML5, CSS3, and JavaScript, ensuring cross- browser compatibility and seamless user experience.

• Translated complex UI/UX wireframes and Figma mockups into reusable Angular components, implementing responsive layouts with Flexbox/Grid for mobile-first design.

• Integrated front-end components with RESTful APIs and microservices, collaborating closely with back-end developers, product owners, and UI/UX designers to deliver business-driven features.

• Utilized Git for version control, Jenkins/GitHub Actions for CI/CD, and SonarQube for maintaining code quality in collaborative team environments.

Software Engineer, Nielsen, TCS 07/2022 – 07/2023 Bangalore, India

• Automated recurring Java tasks, reducing manual workload by 25% and speeding up report generation.

• Delivered 99.9% accurate, time-sensitive radio data across global time zones, boosting client confidence.

• Accelerated processing by 30% through Appworx and AWS Cloud Shell integrations.

• Built responsive, cross-platform front-end interfaces using HTML5, CSS3, JavaScript (ES6), and AJAX, delivering intuitive user experience and real-time interaction with backend services.

• Applied AWS (S3, Lambda, CloudWatch) to automate monitoring and streamline data delivery. Software Engineer, Sonata 05/2021- 06/2022 Remote,India

• Engineered scalable e-commerce backend with Java, Spring Boot, Hibernate, supporting product management, order processing, and authentication.

• Built RESTful APIs for catalog, cart, checkout, and user flows, optimized with efficient JPA/HQL queries.

• Implemented secure authentication/authorization with JWT, RBAC, and input validation, improving API response time by 35% using MySQL query optimization.

Certifications

• AWS Cloud Practitioner

• Google Data Analytics

• Microsoft Azure AI Fundamentals

Academic Projects

• Retrieval Augmented Generation: Developed a LangChain/LlamaIndex-powered system to answer queries from PowerPoint content, elevating retrieval accuracy by 30% through vector similarity scoring and query expansion.

• YouTube video Summarizer: Built a pipeline using yt-dlp, FFmpeg, and CUDA-accelerated Whisper to convert YouTube videos into summaries, achieving over 95% transcription accuracy and reducing manual review time by 70%.

• Cross-Sequence MRI Translation Using DUCK-NET and U-NET: Designed and evaluated DUCK-NET and U-Net with attention mechanisms for cross-sequence MRI translation, achieving a PSNR of 29.4 and SSIM of 0.91, elevating spatial consistency by 15%.

• Web based Book Recommendation System: Devised a web-based Book Recommendation System using collaborative and content-based filtering, boosting recommendation accuracy by 25% and enhancing user engagement through personalized suggestions.

• News Recommendation System Using Prompt Learning: Developed an AI-powered News Recommendation System using Prompt4NR, leveraging prompt learning to deliver context-aware suggestions and improve recommendation accuracy.

Contact this candidate