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Software Engineer with 3+ years in scalable backend systems, AI, and cybersecurity with 3.8 years of
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Final-year Computer Science student with hands-on experience building scalable backend systems, real-time data pipelines, and machine learning-powered security tools. Designed and deployed a Graph Neural Network for Java code vulnerability detection and a full-stack Spotify music automation pipeline with real-time processing. Proficient in system design, API optimization, and integrating ML models into production workflows. Passionate about software engineering at the intersection of backend development, security, and AI.
SRM Institute of Science and Technology
Bachelor of Technology · Computer Science and Engineering
August 1, 2022 – Present
DAV Public School
Class XII · Science Stream
June 1, 2020 – May 31, 2022
Maharishi Vidya Mandir
Class X
June 1, 2019 – May 31, 2020
AI-Based Personalized Learning System
January 1, 2025 – Present
Developed a full-stack AI-powered adaptive learning platform using Flask microservices, React frontend, and JWT authentication. Built AI chatbot assistance, adaptive quizzes, roadmap generation, and personalized course recommendation systems. Integrated Generative AI, semantic search, and scalable microservice architecture for context-aware learning experiences.
View ProjectAI-Powered Java Vulnerability Detection (GNN-based)
January 1, 2024 – Present
Modeled Java source code as AST, CFG, and DFG graphs; trained a GCN to detect SQL Injection and XSS vulnerabilities with accuracy improvements over rule-based static analysis. Integrated the model into Java runtime via DJL and architected CI/CD pipeline support for automated security scanning on every commit.
View ProjectSpotify Intelligent Music Downloader with Auto Playlist Sync
January 1, 2024 – Present
Built a real-time full-stack pipeline with a scoring-based metadata matching engine and multi-source fallback (YouTube, SoundCloud), achieving near-100% download success rate. Reduced Spotify API overhead by 60%+ via intelligent caching and rate-limit handling; added auto-monitoring daemon for incremental playlist sync.
View ProjectCultural Fit Analysis
The candidate's academic projects demonstrate a strong interest in cutting-edge technologies like AI/ML, real-time systems, and security. This aligns well with innovative and technically driven environments. The diversity of projects (security, music automation, personalized learning) shows a broad interest and adaptability. However, the lack of professional experience or team-based project descriptions makes it challenging to fully assess cultural fit regarding collaboration and workplace dynamics.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to tackle complex problems, design scalable systems, and integrate various technologies. The focus on real-time systems, API optimization, and security suggests a detail-oriented and performance-aware approach. However, without direct work experience or psychometric test results, it's difficult to assess collaboration, stress handling, or direct communication skills in a professional setting.