Prince Singh

About

I'm a Founding Engineer & AI Architect with 1.8 years of hands-on experience building AI-native and Full-Stack Systems at scale. Currently leading AI Architecture & Product Development @ProPeers, where I’ve designed and deployed intelligent products like RoadmapAI, AskAI, CodeLLM, and a Contextual AI Code Editor that blend LLMs, RAG, and MCP Protocols to power real-time learning and code intelligence for 100K+ users.I specialize in architecting Agentic AI Ecosystems using Azure OpenAI Service and Azure Databricks Service, combining GPT-based reasoning models, Llama 3.x models, and Databricks-hosted OSS models to build hybrid, scalable, low-latency inference systems. With deep experience in token optimization, context-window compression, and dynamic prompt engineering, I’ve built highly cost-efficient and accurate multi-model pipelines that operate reliably under production workloads.I architect Adaptive RAG Systems blending LangChain, ChromaDB, OpenAI GPT, Llama, and custom vector search pipelines to deliver real-time retrieval (<1s). My work spans MERN + TypeScript, Azure Cloud, Docker/Kubernetes, and end-to-end CI/CD + observability stacks with Prometheus, Grafana, Redis, and async caching pipelines.Beyond engineering, I’ve implemented token-based tiered access systems, designed self-optimizing RAG pipelines, and engineered distributed multi-model inference workflows that scale efficiently under real production traffic. Through advanced SSR, dynamic imports, and hybrid rendering patterns, I’ve reduced response times from 1.1s → 200ms, enabling frictionless, AI-augmented developer experiences.A lifelong Problem Solving & DSA Enthusiast, I’ve solved 5000+ problems, maintained a 1400+ DaysOfCode streak, and ranked in the Top 0.1% worldwide across LeetCode, GFG, and InterviewBit. As a Mentor to 40,000+ learners, I guide aspiring engineers in mastering DSA, Development, DevOps, System Design, and Remote Job Preparation helping them transition from theory to thriving careers.I love designing scalable, intelligent systems, mentoring passionate builders, and shaping the next generation of AI-first engineering culture.

Experience

ProPeers

Founding Engineer

July 2025 – Present · Delhi, India · Remote

▹Led the launch of Roadmap AI, a fully personalized learning assistant powered by RAG (Retrieval-Augmented Generation), OpenAI’s text-embedding-ada-002, Chroma Vector DB, and Modal for real-time, scalable inference.
▹Architected a self-learning dynamic RAG pipeline: [JSON → Embedding → Chroma DB → Query Context Retrieval → Prompt Masking → Model → Nested JSON Output]
▹Dynamically decides whether to retrieve existing context or generate a roadmap from scratch, enabling zero-friction personalization for every user query.
▹Injects prompt templates based on match confidence and automatically re-embeds new data into the vector store making the system truly adaptive and self-updating.
▹Integrated MCP (Modular Content Pipeline) to process and vectorize 100+ roadmaps, enabling semantic search and structured AI roadmap generation.
▹Engineered a Model Context Protocol (MCP) to standardize context injection for the model combining retrieved chunks, user metadata, prompt masks, and query scaffolding ensuring consistent and accurate outputs at sub-second latency.
▹Developed token-based access with one-time/monthly/yearly tiers, including real-time token usage tracking, speed controls, and upsell modals for premium upgrades.
▹Achieved <1s latency for AI responses at scale, improving retention and enabling smooth, conversational AskAI interactions.
▹Built an AI-powered DSA Code Editor supporting Run/Submit/Save, tightly integrated with Roadmap AI and backed by gpt-3.5-turbo, o3-mini, and o1 models for contextual code assistance.
▹Enhanced AskAI with contextual node + discussion integration, improving answer relevance and surfacing smarter suggestions.
▹Resulted in 3x higher roadmap completions, reduced user drop-offs, and transformed the platform into a self-evolving AI-first learning ecosystem.

SDE - 1

July 2024 – July 2025 · Delhi, India · Remote

▹Built and scaled the flagship "Roadmaps" feature, delivering 100+ curated learning paths across DSA, Development, and System Design used by 100K+ users. Improved personalization and relevance, while reducing API response time from 2.1s to < 300ms, resulting in a 7x faster experience and 40% higher user engagement.
▹Worked on complex APIs to reduce processing time and improved tab switching experience for smoother navigation
▹Developed and integrated the "AskAI + Discussion Forum", an intelligent peer-programming assistant where users can interact with AI to solve DSA/Dev doubts and collaborate with others enabling on-demand doubt resolution and community learning.
▹Engineered a Session Recording Bot using Python, Selenium, and headless Azure VMs with deep link automation automating session joining and recording, cutting down 100% of manual effort and improving reliability.
▹Optimized 150+ APIs by implementing advanced caching layers, async processing, and API pipelines, reducing backend latency by up to 70% and improving system throughput.
▹Reduced core web vitals TBT, LCP, and FCP from 4.4s to 990ms through advanced frontend optimizations (SSR, dynamic imports, lazy-loading APIs), significantly boosting UX for 15K+ monthly active users.
▹Led the end-to-end performance overhaul of the platform, focusing on smoother tab-switching experiences, minimal downtime, and blazing-fast navigation across the app.
▹Migrated MongoDB from Atlas to self-hosted replica sets, wrote automated backup & recovery scripts, set up VMs, and integrated cron-based backups to Azure Blob, ensuring data durability and cost-efficiency.
▹Set up real-time monitoring and alerting with Prometheus and Grafana, ensuring system health, proactive issue resolution, and enhanced DevOps visibility.
▹Deployed scalable CI/CD pipelines using Azure, GitLab, and Vercel, ensuring zero-downtime deployments and faster iteration cycles across teams.
▹Handled end-to-end production deployment and scaling for a system serving 15K+ users, maintaining high availability, fault tolerance, and robust performance at scale.

Cloud Conduction

Junior Software Engineer

Jan 2024 – June 2024 · USA, · Remote

▹Built an AI-powered chat application from the ground up using React and .NET, improving frontend efficiency by 60% and backend performance by 30%, delivering a highly responsive user experience.
▹Integrated and optimized AI model responses, reducing latency from 1.86s to 1.2s (35% faster) through strategic API design, caching, and performance tuning.
▹Designed scalable cloud architecture on Microsoft Azure for AI workloads, improving system throughput by 10% while significantly reducing infrastructure costs via autoscaling and resource optimization.
▹Developed modern, responsive UI components in React that improved user engagement metrics by 25%, including better retention and interaction rates.
▹Implemented secure, scalable API gateways in .NET Core, capable of handling 500+ concurrent requests with 99.9% uptime, supporting production-level reliability.
▹Led the implementation of new features using the MERN stack, cutting down development time by 40%, and accelerating product iteration cycles.
▹Established CI/CD pipelines (Azure DevOps & GitHub Actions), reducing deployment failures by 75% and enabling faster, automated releases.
▹Conducted in-depth code reviews and optimization, reducing technical debt by 30%, standardizing best practices across teams, and improving maintainability.
▹Owned and managed the complete project lifecycle, from initial system design and dev planning to production deployment, server setup, and post-launch support.

Impactful Work As a ( INDIVIDUAL CONTRIBUTOR )

INDIVIDUAL CONTRIBUTOR

I've worked across some meaningful projects where I built AI-powered learning tools, smart code evaluation systems, and a real-time AI code editor. I also improved 150+ APIs to make everything faster and smoother for users. This section highlights the key contributions I've made while creating practical, reliable, and user-focused products.

▹Engineered production-grade AI platform serving 100K+ users with personalized learning roadmaps, articles, and practice questions using sophisticated RAG architecture
▹Built intelligent RAG system with Azure OpenAI embeddings and ChromaDB, achieving <1s response times through optimized vector operations and topic-aware filtering
▹Implemented self-learning architecture where AI-generated content automatically enhances knowledge base, creating continuous improvement loop through automated vector updates
▹Developed real-time intent classification with 4 customization types (NEW_SUBADMAP, ADD_TOPICS, PROJECT, REGENERATE) and progress-preserving content merging
▹Architected multi-model AI orchestration with MCP-compliant prompts and dynamic context injection based on user proficiency, difficulty, and learning goals
▹Created enterprise-grade security with multi-layer validation, content safety analysis, technical relevance scoring, and AI-powered verification for edge cases
▹Designed scalable token economy with tiered allocation, operation-based costing (Creation: 2, Customization: 4), and graceful limit enforcement
▹Optimized database performance with comprehensive indexing, efficient session-based queries, and Redis caching for user progress tracking
▹Implemented resilient fallback strategies ensuring 100% availability with graceful degradation when RAG retrieval fails or sparse queries occur
▹Delivered 3x improvement in completion rates through intelligent personalization, real-time progress tracking, and adaptive content generation
▹Built comprehensive progress tracking with real-time state synchronization, bookmarking, notes management, and cross-device persistence
▹Established continuous deployment pipeline with production monitoring, comprehensive logging, error handling, and health check systems