Shubham More
Senior Full Stack Engineer
Software Engineer with 4+ years of experience building scalable web applications using the MERN and PERN stacks. Specializes in designing multi-tenant SaaS architectures, integrating Generative AI workflows with LangChain, and optimizing backend performance with Golang and event-driven AWS services. Experienced in serving 50K+ daily active users across distributed systems.
About Me
I am a Senior Full Stack Engineer specializing in the MERN and PERN stacks, with a strong focus on building scalable, high-performance web applications. My expertise extends to designing multi-tenant SaaS architectures and integrating advanced AI workflows using LangChain.
I have a proven track record of optimizing backend performance with Golang and leveraging event-driven AWS services to handle large-scale data processing. I am passionate about open source and have contributed to major projects like VS Code and React.
Skills
Frontend
Backend
AI & LLMs
Databases & Cache
Cloud & DevOps
Experience
SR Analytics
Full Stack DeveloperApr 2025 – Mar 2026- Engineered a multi-tenant analytics SaaS (Beast Insights) using Node.js and PostgreSQL, implementing Row-Level Security (RLS) to ensure 100% data isolation for 10+ corporate clients
- Designed AI tool-use architectures with LangChain, enabling LLMs to execute controlled REST API calls that automated 60% of repetitive data workflows
- Led the migration of 3 legacy applications to Next.js with SSR and ISR, improving Lighthouse performance scores by 35% and boosting organic search traffic
- Built dynamic filter hierarchies and real-time notification systems using React, Redux, and WebSocket connections for sub-second live dashboard updates
Irys India
Full Stack EngineerFeb 2022 – Apr 2025- Scaled MEVN stack applications to support 50,000+ daily active users by implementing Redis caching, database indexing, and horizontal load balancing
- Re-architected performance-critical backend services in Golang with concurrent goroutines, reducing P95 API latency from 800ms to 200ms on high-load endpoints
- Designed and deployed the organization's first RAG pipeline using LangChain and vector databases, reducing manual document lookup time by 70%
- Architected a multi-tenant Inventory Management SaaS (Tiara Hub) on the MERN stack with strict data isolation, JWT authentication, and automated RFID label printing via ZPL integration
- Optimized infrastructure costs by 40% through migrating background tasks to event-driven AWS Lambda functions triggered by SQS message queues
Projects
LZ-Compress CLI
- Engineered a lossless file compression engine using Huffman tree encoding, achieving 40-65% size reduction across 10K+ test files with zero data loss
- Implemented producer-consumer pattern with goroutines and buffered channels, processing 500MB files in parallel with 3x throughput improvement over sequential compression
VectorFlow Search Engine
- Architected an in-memory vector database supporting 100K+ embeddings with HNSW graph indexing, delivering sub-50ms query latency for Top-K similarity searches
- Optimized nearest-neighbor retrieval using Min-Heap priority queues and cosine distance calculations, powering RAG pipelines with 95% relevance accuracy
RateGuard API Gateway
- Built a distributed rate limiter middleware using Token Bucket algorithm with Redis-backed atomic counters, protecting APIs from 99.8% of abusive traffic patterns
- Designed sliding window rate tracking with O(1) HashMap lookups and mutex-protected state synchronization, handling 10K+ requests/second per endpoint
AnomalyStream Analytics
- Developed real-time transaction fraud detection processing 15K+ events/second using sliding window moving averages and Z-score anomaly thresholds
- Implemented graph cycle detection with DFS traversal to identify circular payment schemes and Trie-based autocomplete for instant merchant search across 2M+ records