HPHarsh PanchalFull-stack · Applied AI
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HPHarsh PanchalFull-stack · Applied AI

Full-stack and applied AI engineer building dependable platforms, secure APIs, data-rich products, and responsive user experiences.

harshpanchal2103@gmail.com Jersey City, NJ

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© 2026 Harsh Panchal. All rights reserved.

Next.js · TypeScript · MongoDB · Node.js 24

Available for selected full-time and contract opportunities

Harsh Panchal · Jersey City, NJ

Full-stack engineering for products that need to work beautifully.

I design and build secure backend systems, responsive web applications, data-rich dashboards, and practical AI features from architecture through production delivery.

View selected work Discuss an opportunity GitHub
Backend architecture and secure APIs Responsive product and admin interfaces Applied AI, RAG, and automation Cloud-ready delivery and testing
Harsh Panchal
Current direction

Reliable product systems, applied AI, and high-quality full-stack delivery.

5+

Years building products

20+

Projects and platforms

4

Engineering specialties

Core stackJavaSpring BootNext.jsReactTypeScriptNode.jsNestJSMongoDBPostgreSQLDockerREST APIsRAGApplied AIData Analytics

How I contribute

From unclear requirements to dependable systems.

I combine backend depth, product thinking, and interface craftsmanship so the result is useful to customers and maintainable for the team.

01

Backend systems

Secure APIs, authentication, data models, integrations, and scalable services across Java, Node.js, SQL, and MongoDB.

02

Full-stack products

Responsive web products, admin platforms, workflow tools, and dashboards built with React, Next.js, and TypeScript.

03

Applied AI

RAG experiences, LLM workflows, AI-assisted product features, prompt systems, and practical automation.

04

Production quality

Security, accessibility, performance, testing, deployment discipline, and maintainable documentation.

Delivery approach

Clear process. Fewer surprises.

01

Clarify

Translate business goals and ambiguity into a focused product and technical plan.

02

Build

Deliver the full path from data model and APIs to polished, responsive interfaces.

03

Harden

Test, secure, document, optimize, and prepare the system for real users and deployment.

Selected work

Projects designed around measurable outcomes.

A closer look at the product problem, engineering decisions, technology, and delivered value.

View all projects
Mango AnalyticsCase study 01

web

Mango Analytics

Developed MangoAnalytics.ai, a modern, responsive corporate website to showcase Mango Analytics’ offerings in AI product development, data engineering, AI/IT consulting, compliance & security, and talent/training programs. Built a clear service-led information architecture (Solutions/Industries/Labs/Training) with strong CTAs (demo/consultation/training) and credibility sections like results and testimonials.

Next JSHTMLCSSJavaScript
Shree NirmalaCase study 02

web

Shree Nirmala

The Sahajayoga Ahmedabad project is a spiritual website designed to spread awareness about Sahaja Yoga meditation and Shri Mataji’s teachings. It aims to help visitors learn meditation, understand chakras, and connect with local meditation centers in Ahmedabad.

Krishna RecruitmentCase study 03

web

Krishna Recruitment

Krishna Recruitment is a modern HR and staffing platform designed to connect skilled candidates with top employers efficiently through data-driven recruitment solutions. It streamlines the hiring process with smart matching, applicant tracking, and personalized career guidance.

Writing & field notes

Ideas shaped by real implementation.

Practical notes on software architecture, applied AI, full-stack delivery, data products, and engineering quality.

Browse all articles
01
AIApr 13, 2026

How to Evaluate an AI Feature Before Releasing It

Learn how to evaluate an AI feature before launch using quality, safety, fairness, robustness, and business metrics.

02
AIApr 6, 2026

Prompt Engineering for Real Product Use Cases

Learn how prompt engineering works in real AI products, with practical use cases, best practices, risks, and a framework for building reliable features.

03
AIMar 30, 2026

How to Add RAG to a Real Product

Learn how to add RAG to a real product with a practical, production-focused approach covering architecture, retrieval quality, security, evaluation, and rollout strategy.

Let's build something useful

Need an engineer who can move from architecture to polished delivery?

Share the product, platform, or engineering challenge. I'll respond with a clear next step.

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