I am a Software Engineer specializing in cloud-native microservices and distributed application development. My expertise lies in backend development with extensive experience in Java, Node.js, and Go, alongside frontend work with React.js. I am passionate about delivering scalable, high-performance code, building secure RESTful APIs, and crafting reliable utilities following Agile methodologies.

Throughout my career, I have led projects that significantly boosted customer engagement and improved user experience. I am also deeply interested in Data Structures, Algorithms, and AI, particularly in the realm of Large Language Models (LLM).

• Role: Full Stack Software Engineer
• Duration: Sep 2024 – Present
• Contributions:
  • Developing core web feature for Health.ai, an AI-powered health chat application and appointment scheduling system with doctors.

• Role: Software Engineer II
• Duration: Aug 2021 – Aug 2022
• Contributions:
  • Led the development of analytic tools that boosted customer engagement by 2.5%.
  • Developed a POC for a product recommendation feature, increasing adoption by 2%.
  • Engineered and deployed interactive features for Adobe Experience Manager (AEM) eCommerce.

• Role: Software Engineer II
• Duration: May 2017 – Jul 2021
• Contributions:
  • Developed Node packages for web accessibility, achieving 35k downloads within the first month.
  • Led the redesign and integration of the friends' management feature on my.playstation.com.

• Role: Software Engineer
• Duration: Oct 2015 – Mar 2017
• Contributions:
  • Developed automation protocols for networking layers, significantly reducing manual efforts.

• MS in Computer Science - Boston University (Sep 2022 – May 2024)
• BTech in Computer Science - VIT University, India (May 2011 – May 2015)

Description: This project explores and compares the performance of machine learning algorithms executed on classical and quantum computers. It investigates the potential performance benefits of quantum computing over traditional classical machine learning approaches in terms of accuracy and execution time.

• Technologies: IBM Quantum Experience, Qiskit Aqua, Python, Scikit-learn, UCI ML Breast Cancer Wisconsin (Diagnostic), UCI ML Wine Dataset

Description: A data warehousing project on the Chicago food database using Apache Airflow, Snowflake, and Grafana for data visualization.

• Technologies: SQLAlchemy, Apache, Snowflake, Data Visualization, Apache Airflow, Grafana, Python

Description: An expense monitoring system for personal and group expenses.

• Technologies: Node.js, JavaScript, Python, Flask, React.js, RESTful API

Description: Performance analysis of Large Language Models (LLMs) on CPU, GPU, Execution Time, and Energy Usage.

• Technologies: JavaScript, MySQL, Java, Spring Boot, React.js, Flask-RESTful, HumanEval

Description: A repository for trying and testing new ideas and technologies.

• Technologies: Various (Experimentation Repository)

Description: Machine Learning model for finding suitable player replacements in FIFA.

• Technologies: Various

Description: A personal movie database portal.

• Technologies: React, JavaScript, Material UI, The Movie Database (TMDb) API, MongoDB, Express.js.

Description: A repository for Data Structures and Algorithms practice.

• Technologies: Various

• LinkedIn: My LinkedIn Profile