Build the product. Understand the system.
I use MERN, Node.js, React, Rust, Python, and GenAI to turn product needs into useful software—from the interface people use to the services and workflows behind it.
Hi, I’m Nishant.
I connect product needs, user experience, and engineering to build software people can use.
I’m Nishant Kumar, a product engineer building complete web products, reliable services, and practical AI workflows. I work across MERN, React, Node.js, Rust, Python, and GenAI to choose what each problem needs—and take it through to a usable solution.
My toolkit includes MongoDB, Express, React, and Node.js (MERN), alongside Next.js, Rust, Python, and GenAI. I can contribute across interfaces, services, data, and automation to deliver a complete solution that a team can understand, maintain, and improve.
A construction workforce portal at TechTown Properties, alongside personal projects spanning full-stack applications, Rust systems, and AI-assisted workflows.
B.Tech, Engineering
Aryabhatta Knowledge University, Patna
TechTown Properties
FreelanceBuilding a construction workforce portal across Next.js interfaces, Rust/Axum services, and AWS EC2 deployment.
Darklake Labs
ContractDeveloped React interfaces and Rust backend services, integrating APIs into end-to-end product features.
Turbin3
FellowshipPracticed Rust systems fundamentals, Solana development, testing, and debugging through hands-on work.
ZERON
EmploymentBuilt reusable React and TypeScript interfaces and Node.js/Express API features across the application stack.
TeamCognito
EmploymentContributed frontend features with JavaScript, React, TypeScript, and Material UI in a collaborative Git workflow.
Useful at more than one layer.
Turn a product need into a feature a team can run, understand, and extend.
Product engineering
Turn a user need into a complete feature, connecting clear interfaces, APIs, and data so a team can ship and improve the product.
Backend engineering
Turn product requirements into clear APIs, async services, and dependable data flows.
AI engineering
Make information easier to use with source-grounded answers, LLM integrations, and practical automation.
Performance & reliability
Design for slow dependencies and failures with bounded concurrency, timeouts, and clear error handling.
Practical choices. Clear ownership.
Start with the actual problem.
Understand the workflow and constraints before choosing the technology. A useful feature matters more than a fashionable stack.
Make boundaries explicit.
Keep interfaces, services, and data responsibilities understandable. Treat authentication, failure handling, and configuration as part of the feature.
Validate the behavior.
Use tests, debugging, and observed results to support a claim. Explain what has been checked and what still needs evidence.
Have a problem worth solving?
Let’s build the right solution.
Tell me what you’re building, who it’s for, and where you need help. Whether it’s a product to launch, a workflow to improve, or an engineering role on your team, let’s work through the next step.
technishant108@gmail.com