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Node JS Developer with less than a year in Distributed Systems & AI/ML
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Backend Engineer with hands-on experience building distributed systems, real-time data pipelines, and high-throughput REST APIs. Independently built and deployed 4 production-grade systems using Node.js, Apache Kafka, Redis, and BullMQ handling 200+ concurrent requests with sub-200ms latency. Strong in System Design (HLD/LLD), microservices, and event-driven architecture. Solved 850+ DSA problems; Top 3 on Coding Ninjas Master League. Open to Remote / Relocation.
Graphic Era Hill University
Bachelor of Computer Applications (BCA) · Computer Applications
August 1, 2023 – June 30, 2026
Masters' Union
Senior Secondary (XII) · Commerce
March 31, 2022 – May 31, 2023
Mini S3
June 1, 2026 – Present
Engineered S3-compatible distributed file storage handling 100+ concurrent requests with response time under 125ms. Built signed-URL authentication (5-min expiry) and achieved 75% cache hit rate using Redis multi-layer caching. BullMQ-based async virus scanning via VirusTotal API — completes in under 30 seconds with auto-retry and dead-letter handling. Supports files up to 500MB with load balancing, permission control, and parallel Redis Pub/Sub worker execution.
View ProjectTruthGuard
June 1, 2026 – Present
Built two-stage AI analysis pipeline achieving 85% accuracy using Groq LLM with Google Search API cross-verification across 20+ sources. Scaled to 50+ concurrent requests; voice output generated in under 1 minute for 500 words via ElevenLabs TTS. Credibility scoring engine with cross-verification algorithms; security stack: JWT, rate limiting, CORS, input validation.
View ProjectClient Pulse
June 1, 2026 – Present
Multi-platform feedback automation handling 200+ concurrent requests with response time under 200ms. Built voice pipeline (Whisper STT + ElevenLabs TTS) generating 100 words in under 45 seconds; 65% cache hit rate via Redis. Integrated Groq AI + Google Sheets API for automated feedback collection and analysis across WhatsApp and Telegram 100% automated.
View ProjectTraceMind
June 1, 2026 – Present
Architected a real-time distributed tracing system using Kafka topics to ingest service-level events across microservices with millisecond-level lag. Built Redis-backed hot-path caching and aggregation layer reducing repeated query latency by ~70% for frequently accessed trace spans. Integrated Groq AI for intelligent anomaly detection — auto-flags error spikes, latency regressions, and dependency failures without manual rules. Designed Kafka consumer groups with partition-level processing for horizontal scale-out; handles 500+ events/sec in benchmarks. Live dashboard delivers service health, trace timelines, and AI-generated incident summaries, reducing MTTR for distributed failures.
View ProjectNode.js (Intermediate)
HackerRank
June 1, 2026 – Present
Software Engineer
HackerRank
June 1, 2026 – Present
Data Structures in C++
Scaler Topics
June 1, 2026 – Present
Computer Networks
Scaler Topics
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's portfolio showcases a strong passion for backend and distributed systems, aligning well with a Node.js Developer role. The diversity of projects, from distributed tracing to file storage and AI pipelines, indicates a broad technical interest and willingness to tackle varied challenges. Their self-taught approach and competitive programming success suggest a proactive and driven individual. However, the lack of team-based project experience or professional roles means cultural fit regarding collaboration and corporate environment adaptability is largely unassessed.
Soft Skills & Operational Fit
The candidate demonstrates strong initiative and self-learning capabilities, having independently built and deployed multiple complex systems. Their competitive programming achievements suggest strong problem-solving skills. The project descriptions indicate an ability to work with real-time data, high-throughput systems, and performance optimization. However, without direct work experience, their operational fit in a team environment and handling of production incidents under pressure is yet to be validated.