const vikash: Engineer = { name : "Vikash Kumar", role : "Full Stack & React Native Engineer | Software Engineer @Sewacity", education : "B.Tech CSE-IoT @GEC Siwan, Bihar | May 2026 | CGPA: 7.48", available : true, targeting : ["SDE-1", "Full Stack", "React Native", "Backend", "AI-Integration"], production : { company : "Sewacity Technologies Pvt Ltd", role : "Software Engineer — May 2026 to Present", users : "10,000+", transactions : "2,000+ / month", playStore : "https://play.google.com/store/apps/details?id=com.sewacity.sewacity", reliability : "+40% payment success via Razorpay webhook orchestration", security : "-60% unauthorized access via JWT/RBAC + rate limiting + DDoS", failures : "-30% payment failures via retry logic + reconciliation", integrity : "100% transaction integrity via server-side HMAC-SHA256 verification", }, rider_module : { status : "Production — May 2026 to Present", app : "React Native (Expo EAS) + Node.js/Express backend", database : "MySQL with Sequelize ORM + Haversine geospatial dispatch", scheduling : "BullMQ repeatable jobs for shift reminders (Redis-backed)", ai_chat : "SevaSaathi — 5-provider fallback (Cerebras → Groq → Gemini → OpenRouter → Cloudflare Workers AI)", i18n : "Centralized language preference system", apk : "https://drive.google.com/file/d/1aj862cX7lh-GpC9-WTjROHragQtl3g7b/view", }, stack : { languages : ["TypeScript", "JavaScript", "C++", "HTML", "CSS", "SQL", "NoSQL"], frontend : ["React", "Next.js", "Tailwind CSS", "shadcn/ui", "Zustand", "Redux"], backend : ["Node.js", "Express.js", "REST APIs", "BullMQ", "Sequelize ORM", "JWT/RBAC"], mobile : ["React Native", "Expo EAS", "Firebase OTP", "AAB/IPA signing", "TestFlight"], database : ["MySQL", "MongoDB", "Redis", "PostgreSQL", "Supabase", "GridFS"], cloud : ["AWS EC2/S3/Route53", "Docker", "NGINX", "PM2", "CI/CD"], ai : ["MCP Protocol", "LLM SDK Integration", "Multi-Provider Fallback", "Claude AI"], }, dsa : "400+ problems | C++ | LeetCode + GeeksforGeeks + Codeforces", hackathons : ["IIT BHU Shilp'24 - 2nd Place (50+ teams)", "TechKshitiz GEC Siwan - 1st Place"], leadership : "Technical Team Lead @Codex Club, GEC Siwan — 20 months", vision : "SDE-1 → Senior Engineer → CTO / Technical Co-Founder", };
Not a chatbot wrapper. Real architectural integration of AI and LLM reasoning into production systems via MCP Protocol - the same pattern powering Claude, Cursor, and next-gen AI tooling.
User Input → LLM (Claude/GPT) → MCP Protocol → Tools / APIs / DB / IoT → Result
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Natural Reasoning JSON-RPC 2.0 MongoDB • Redis Structured
language over live Tool contracts RFID • REST output back
prompt context (Host→Client→Server) Sensors • GridFS to product UI
My AI Integration Stack
How I use each tool in my actual workflow:
- Claude AI - architecture decisions, writing technical documentation, code review, system design walkthroughs, and MCP server implementation. I don't use it to write code blindly - I use it to think through design tradeoffs before touching the keyboard.
- ChatGPT - quick syntax fixes, exploring multiple approaches to the same problem, rubber-duck debugging on unfamiliar APIs, generating test cases.
- GitHub Copilot - in-editor code completion, reducing boilerplate in repetitive patterns (route handlers, schema definitions), and surfacing API signatures mid-flow.
- Antigravity AI Editor - AI-native editor for faster development loops with embedded LLM assistance.
MCP in production (Academic Management System):
// MCP Server: academic-intelligence // Architecture: Host (Claude) → MCP Client → MCP Server → MongoDB + RFID sensors // Transport: JSON-RPC 2.0 over stdio const tools = [ { name: "get_student_recommendations", // LLM receives live student context → reasons → returns structured suggestions // Zero prompt leakage. Typed contracts. Auditable tool calls. }, { name: "analyze_performance_patterns", // Connects LLM reasoning to MongoDB aggregation pipelines directly } ]; // Result: AI-powered personalized resource recommendations running in production // User → LLM → MCP → MongoDB + RFID → Personalized response
| Metric | Result | How |
|---|---|---|
| Users Served | 10,000+ | Web platform + React Native app (Play Store) |
| Monthly Transactions | 2,000+ | Razorpay payment pipeline |
| Payment Reliability | +40% | Webhook orchestration + retry logic + idempotency |
| Order Growth | +36% | Latency-optimized REST APIs + geo-aware backend |
| Unauthorized Access | -60% | JWT/RBAC + rate limiting + DDoS safeguards |
| Payment Failures | -30% | Failure reconciliation layer + dead-letter logging |
| Transaction Integrity | 100% | Server-side Razorpay HMAC-SHA256 verification |
| GitHub Contributions | 2,132 | Last 12 months - consistent daily engineering |
Languages
Frontend
Backend
Database
Mobile (React Native)
Cloud, DevOps & Infrastructure
Developer & Productivity Tools
Figma: I read and implement designs, convert component specs to production-ready code. Design creation is not my primary strength - shipping designs as pixel-accurate components is.
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Sewacity Mobile App - iOS + Android
Production React Native app - 10K+ users, 2K+ monthly orders. Redux state, Firebase OTP auth, server-side Razorpay verification, real-time order tracking, geo-location. Expo EAS builds with AAB signing (Play Store) and IPA distribution (Apple Dev Console + TestFlight). |
SafeExec - Enterprise RCE Platform
Secure open-source Remote Code Execution platform. Every execution runs in an isolated Docker container - no shared state. Redis job queue for scalable throughput. Multi-language support (Python, JS, Java, C++, C#, Go). Swagger UI docs. Built for exam platforms, hiring tools, online judges. |
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Contest & Event Management Platform
Built for TechKshitiz, GEC Siwan - ran a live contest for 300+ students simultaneously in production. Automated seating assignment, participant verification, integrated code editor, real-time test workflows. Designed to scale to institutional exam bodies. |
Academic & Library Management System (AI + IoT)
Campus management with RFID automation, MCP-based LLM recommendation engine, layered RBAC, coursework workflows, scheduling, and digital repository. Real MCP server implementation connecting LLM reasoning to live MongoDB + IoT sensor data. |
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MongoDB GridFS Bucket System
Open-source file storage API on MongoDB GridFS. Store, stream, and manage large files via a clean REST interface. Documented and production-ready. Solves the S3-overkill problem for small-to-medium file management. |
Portfolio v3 - Production SPA
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Problem → Decompose → Data Model → API Contract → Security Layer → Fault Paths → Ship
Real example @Sewacity - Razorpay Webhook Reliability
──────────────────────────────────────────────────────
Problem : Payment status inconsistency - client-side verification unreliable
Root : No idempotency, no retry on failures, no reconciliation job
Solution : Server-side HMAC-SHA256 signature verification
+ Idempotency key per webhook event
+ Redis retry queue with exponential backoff
+ Cron-based failure reconciliation job
+ Dead-letter log for manual audit trail
Result : +40% transaction success, -30% failures, 100% integrity
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50+ competing teams - full-stack solution under time pressure |
GEC Siwan - led and won the hackathon |
TechKshitiz org, GEC Siwan |
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DNS, SSL, production server management |
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Funded Startups (Seed / Series A) Full stack from mobile to infra. Built for 10K+ users as a solo contributor. I don't wait for tickets - I find bottlenecks, scope the fix, and ship. Built for early-stage velocity where every engineer counts. |
MNCs and Product Companies Security-hardened APIs, event-driven design, fault-tolerant webhook systems. Docker, AWS, CI/CD, NGINX in production. Strong DSA foundation (400+ problems). Code that survives proper code review. |
AI-First Products I understand MCP protocol architecture end-to-end - not just API calls. I've shipped LLM-driven features in production with real data contracts and typed tool schemas. No brittle prompt hacks. |
Open for → SDE-1 / Full Stack / React Native / Backend roles
Shipping → Rider module (RN app + backend) — production at Sewacity
Building → SevaSaathi AI chat (5-provider free-tier LLM fallback chain)
Leading → Junior developer team — architecture + implementation direction
DSA → Medium → Hard (Graphs, DP, System Design)
Vision → SDE-1 → Senior Engineer → CTO / Technical Co-Founder
Open to SDE-1, Full Stack, React Native, and Backend roles at startups and product companies.
Vikash Sharma - Built with intent. Every commit ships toward production.