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Software Engineer with 4+ years in Node.js, React.js & AI/ML
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Full Stack Software Engineer experienced in building scalable REST APIs, distributed systems, and AI-powered applications using Node.js, TypeScript, React.js, Vue.js, PostgreSQL, and Express.js. Skilled in system design, microservices architecture, performance optimization, reliability engineering, and scalable backend development for enterprise and product-driven applications.
Indian Institute of Technology (IIT) Ropar
M.Tech · Computer Science and Engineering
August 1, 2022 – June 30, 2024
Noida Institute of Engineering and Technology
B.Tech · Computer Science and Engineering
August 1, 2016 – June 30, 2020
HCL Software
Senior Software Engineer
July 1, 2024 – Present
Noida, Uttar Pradesh, India
Tata Consultancy Services
Assistant System Engineer
January 1, 2021 – July 1, 2022
Lucknow, Uttar Pradesh, India
Kolliq - AI-Powered Creator Analytics & Recommendation Platform
June 19, 2026 – Present
Built an AI-powered influencer-brand matching platform using Vue.js, Node.js, PostgreSQL, REST APIs, LLM APIs, and microservices architecture to automate creator discovery and campaign workflows. Designed and implemented a scalable recommendation engine using creator metadata, engagement analytics, campaign requirements, and LLM-powered reasoning, reducing manual shortlisting effort by ~70%. Developed modular backend services, distributed AI orchestration pipelines, and PostgreSQL database models to support creator analytics and recommendation workflows. Implemented scalable REST APIs, async workflow handling, caching strategies, and backend optimization techniques for high-performance distributed systems. Designed and developed production-ready frontend dashboards, backend APIs, database models, and AI service integrations for scalable creator analytics workflows.
Dynamic K-Means Based Round Robin CPU Scheduling Algorithm
June 19, 2026 – Present
Implemented an optimized CPU scheduling algorithm using K-means clustering to dynamically adjust time quantum values during each scheduling cycle. Improved CPU resource allocation efficiency by adapting scheduling behavior according to process burst-time characteristics and workload distribution. Analyzed algorithm performance using scheduling metrics such as turnaround time, waiting time, and CPU utilization. Applied concepts from Operating Systems, Algorithms, and Machine Learning to design an adaptive process scheduling mechanism.
Competitive Programming: Solved 1000+ DSA problems across LeetCode, CodeChef, and Codeforces with highest ratings of 1786 on LeetCode, 1631 on CodeChef, and 1321 on Codeforces.
Unknown
June 1, 2026 – Present
Research Publication: Published research paper in IEEE Geoscience and Remote Sensing Letters on unsupervised crop classification using deep learning and satellite time-series data.
IEEE Geoscience and Remote Sensing Letters
June 1, 2026 – Present
Conference Acceptance: Research work titled End-to-End Land Cover Classification accepted for demo presentation at the International Conference on Agriculture Centric Computing (ICA-23).
International Conference on Agriculture Centric Computing (ICA-23)
June 1, 2026 – Present
GATE CS 2021: Secured 98.9 percentile, ranking among the top 1.1% candidates nationwide.
Unknown
January 1, 2021 – Present
Cultural Fit Analysis
The candidate demonstrates a strong cultural fit through diverse project experiences (AI-powered platform, CPU scheduling algorithm), academic achievements (IIT Ropar, research publications), and competitive programming success. Their roles as a Teaching Assistant and Executive Council Member indicate a collaborative spirit and willingness to contribute beyond core technical tasks. The breadth of skills across frontend, backend, databases, AI/ML, and DevOps suggests adaptability and a continuous learning mindset, which are valuable for cultural alignment.
Soft Skills & Operational Fit
The candidate's resume highlights contributions to agile development environments, debugging production issues, and improving system reliability, suggesting good operational fit. Involvement in student governance and teaching assistant roles indicates leadership potential and communication skills. The detailed project descriptions and experience show a proactive approach to problem-solving and a focus on efficiency improvements.