I’m a full-stack engineer with 3.5+ years of hands-on experience building and scaling production-grade web platforms, currently pursuing a Master’s in Computer Science in the U.S.

I’ve worked in product-driven companies and startup-style teams, where engineering decisions directly impact performance, scale, and real users. My experience spans high-performance frontend systems, scalable backend services, and cloud-native infrastructure, with a strong focus on AI-powered applications and DevOps-driven systems.

I enjoy solving real problems — optimizing performance, simplifying architecture, and building systems that hold up under scale.

• 3.5+ years in product-based environments (Bajaj Finserv Health, RadioFX)
• Owned and maintained high-traffic B2C modules driving ~98% of platform traffic
• Improved SEO, Core Web Vitals, and page performance using SSR, caching, and optimization techniques
• Built end-to-end full-stack platforms (frontend + backend) used by internal teams and partners
• Designed and deployed cloud-native systems on GCP (GKE, Kubernetes, CI/CD, Artifact Registry)
• Developed secure, plug-and-play APIs for third-party integrations
• Integrated AI / LLM-powered features into production systems

• Full-Stack Engineering
  React.js, Next.js, Node.js, NestJS, Python, SQL, MongoDB
• Performance & Scalability
  SSR, caching strategies, micro frontends, system optimization
• Cloud & Distributed Systems
  GCP, Kubernetes (GKE), Docker, CI/CD pipelines
• AI & Applied Machine Learning
  LLM-powered applications, automation, intelligent workflows
• DevOps & Platform Engineering
  Infrastructure automation, reliability, observability
• Crypto & Stock Market Analysis
  Technical and fundamental research

• Applied AI & LLM Systems
  Designing and integrating AI/LLM-powered features into real-world applications, focusing on automation, intelligent workflows, and system-aware behavior
• Full-Stack Product Engineering
  Building end-to-end applications using React/Next.js, Node/NestJS, and databases, with emphasis on performance, maintainability, and scalability
• AI Infrastructure & MLOps Foundations
  Containerizing, deploying, and scaling AI workloads using cloud-native and DevOps best practices
• DevOps & Cloud Infrastructure
  Designing and operating production-grade infrastructure on GCP, with deep focus on Kubernetes (GKE), networking, ingress, secrets, and security
• Scalable CI/CD Platforms
  Building reusable and efficient CI/CD pipelines using GitHub Actions and Cloud Build, optimized for speed, cost, and multi-environment deployments
• Distributed & Event-Driven Systems
  Architecting resilient systems using async communication, queues, and pub/sub patterns
• Reliability, Observability & Security
  Implementing logging, monitoring, alerting, and reliability patterns for large-scale systems

• AI- and LLM-powered products with real-world impact
• Full-stack applications that prioritize performance, scalability, and clean architecture
• AI infrastructure, MLOps, and platform engineering initiatives
• DevOps-heavy and cloud-native systems (Kubernetes, CI/CD, infra automation)
• Scalable backend and distributed systems
• Open-source projects in AI tooling, developer platforms, or cloud infrastructure

• 📧 Email: prathik0300@gmail.com
• 🌐 Portfolio: https://www.prathikpugazhenthi.dev
• 💻 HackerRank: https://hackerrank.com/prathik0300
• 🧠 LeetCode: https://leetcode.com/prathik0300

• Python
• JavaScript / TypeScript
• SQL

• Frontend: React.js, Next.js, HTML5, CSS3
• Backend: Node.js, NestJS, Express.js

• GCP, Azure, AWS, Kubernetes (GKE), Docker
• CI/CD (GitHub Actions, Cloud Build)

• PostgreSQL, MongoDB, Redis, Cassandra

• Power BI, Google Analytics, Alteryx

Building systems that scale. Optimizing what matters.
Always learning. Always shipping 🚀