Building Autonomous AI Agents • RAG Pipelines • Scalable Microservices
🏆 3rd Place Winner — MotiaHack’25
💼 Open to Backend & GenAI Engineering Roles
I build production-ready Agentic AI systems that go beyond chat — they execute workflows, automate decisions, and scale reliably.
Core Focus Areas:
- Autonomous AI Agents
- Model Context Protocol (MCP) Systems
- Retrieval-Augmented Generation (RAG)
- Scalable Node.js Microservices
⭐ “The future of software isn't just a chatbot — it's an adaptive interface generated on demand.”
MotiaHack’25 Winner
- Log monitoring & crash detection
- AI-suggested codebase fixes (Gemini)
- Human-in-the-loop validation
- Backend orchestration system
Natural Language → Production-ready API
- Backend generation from prompts
- Automated testing & deployment
- CI-integrated review workflow
- Dynamic React UI surfacing
- Context-aware interface generation
- Built with Tambo AI
- Secure local file indexing
- Automatic PII redaction
- Controlled context exposure
- AI-based resume detection
- Automated candidate extraction
- Reduced manual workload by 40%
AI & LLMs:
OpenAI • Claude • Gemini • Ollama
Backend:
Node.js • Express • TypeScript • JavaScript
Databases:
PostgreSQL • MongoDB • MySQL • Redis
DevOps:
Docker • AWS • Kestra • CI/CD • n8n
- Built AI Email Mining & Outreach Automation System
- Reduced marketing workload by 40%
- Designed scalable microservices (Node.js + TypeORM + MySQL)
- Architected REST APIs
- Contributing to text-only social platform
- Built with Next.js & GraphQL
🔗 LinkedIn: https://linkedin.com/in/shubham-01-star
📧 Email: shubhamkumar990201@gmail.com