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Hi, I'm Parth Bhardwaj 👋

DevOps Engineer  ·  Backend & AI Developer  ·  Cloud Enthusiast

Building scalable systems, intelligent backends, and production-grade cloud infrastructure.

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$ whoami

name:      Parth Bhardwaj
role:      DevOps Engineer · Backend & AI Developer
stack:     Go · Node.js · Python · Kubernetes · Docker · GCP · AWS
focus:     Scalable systems · Microservices · LLM Integration · Cloud Infra
portfolio: https://portfolio-website-chi-sooty-71.vercel.app
email:     parthbhardwaj2579@gmail.com
goal:      High-paying remote engineering role (500K+)
mindset:   "Execution > Motivation"

---

$ cat about.md

Backend & AI Engineer focused on building scalable backend systems and intelligent, data-driven applications using Go (Golang), Node.js, and Python. Experienced in designing REST APIs and microservices architectures, with hands-on exposure to Docker, CI/CD pipelines, and cloud-based deployments.

Skilled in developing database-driven systems using PostgreSQL and MongoDB, with a strong focus on performance, system design, and maintainability. Interested in integrating AI and automation into backend services to build efficient, production-ready systems.

• 🔭 Currently focused on DevOps, Kubernetes, and Cloud Infrastructure
• 🌱 Learning Go (Golang), System Design, and Advanced Kubernetes
• ⚡ Building skills in Docker, CI/CD, Microservices, LLM Integration, MCP
• 🎯 Goal: Land a high-paying remote engineering role (500K+)
• 💡 Mindset: Execution > Motivation

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$ ls ./tech-stack

💻 Languages
⚙️ DevOps & Cloud
🗄️ Databases
🤖 AI & Emerging
🔧 Tools

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$ cat projects.json

🤖 AI-PM AI-powered product ideation tool that transforms raw ideas into structured, actionable insights. Leveraged MCP (Tambo) to auto-generate reusable Next.js UI components, cutting manual frontend effort Integrated Groq LLM for product breakdowns, use cases & feature suggestions Combined component-driven frontend automation with AI-powered decision support View Project →

🏗️ APNCODIX Full-stack production platform built from scratch with real-world deployment practices. Frontend: Next.js 14, React, TypeScript, Tailwind + Radix UI Backend: NestJS + PostgreSQL (Prisma), JWT auth, rate limiting DevOps: Docker + Nginx on VPS, HTTPS via Let's Encrypt, GitHub Actions CI/CD Integrations: Cloudinary (media), Razorpay (payments) ⚡ Achieved 100/100 on Google PageSpeed Insights View Project →

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$ tail -f current-focus.log

[01] Kubernetes Internals .......... API server · kubelet · scheduler
[02] Go Microservices .............. Building & deploying production services
[03] CI/CD Pipelines ............... GitHub Actions & automated deployments
[04] Cloud Architecture ............ GCP + AWS for scalable systems
[05] System Design ................. Designing for scale and reliability
[06] LLM Integration ............... AI-powered backend services via MCP

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$ curl api.github.com/users/parthbhardwaj7/stats

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$ cat connect.sh

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> "You don't get paid for effort. You get paid for value."

⚡ Always building. Always shipping.