Technical support · Customer-facing engineering

Mohit Kumar.

Technical Support Specialist with a Computer Science degree. I bridge engineering and customer impact—debugging APIs, tracing integrations, reproducing issues, and building tools that make systems reliable. Moving toward Technical Support Engineer and junior software engineering roles.

Contact me

View my work ↓

About

How I work

I work alongside engineering teams to resolve complex, customer-impacting problems: API and webhook failures, third-party integrations, DNS and email authentication (SPF, DKIM, DMARC), and escalations that need clear, reproducible evidence.

My background is technical support with a CS foundation—comfortable reading logs, testing hypotheses, and communicating trade-offs to both engineers and customers. Outside tickets, I build full-stack applications, ML projects, and automation to sharpen my engineering craft.

Skills

Stack & domains

Languages

JavaScript
TypeScript
Python
HTML5 / CSS3

Frameworks & libraries

React
Next.js
Node.js
Tailwind CSS

APIs & integrations

REST APIs / webhooks
OAuth 2.0
Postman
DNS / SPF / DKIM / DMARC

Data & ML

Scikit-learn
Pandas
Streamlit

Tools & workflow

Git
Issue reproduction
Technical writing & escalations

Experience

Professional background

Own technical troubleshooting and escalation triage for customer-facing issues—translating symptoms into actionable next steps.
Debug API requests, webhook payloads, and third-party integration failures across environments.
Investigate DNS and email authentication problems (SPF, DKIM, DMARC) and document resolutions for customers and internal teams.
Reproduce customer-reported bugs, capture repro steps, and hand off clear packages to engineering.
Partner with engineering and product on cross-functional resolution, communication, and follow-through until closure.

View project

View code

NBA All-Star Predictor

Problem: All-Star selection is high-stakes and opaque; stakeholders need a data-driven view of who is likely to make the cut. Approach: Built an ML classifier on historical player stats with feature engineering and model comparison in Scikit-learn, shipped as an interactive Streamlit app for exploration. Impact: Demonstrates end-to-end data science: wrangling, evaluation, and a deployable surface for non-technical users.

Python

Scikit-learn

Streamlit

Pandas

View project

View code

View project

View code

Ride1Up e-commerce experience

Problem: Real storefronts require coherent routing, state, and presentation across many product flows. Approach: Cloned a production-style bike e-commerce UX with React Router and Redux for predictable global state, and CSS Modules for maintainable styling boundaries. Impact: Shows how I structure larger frontends—not just pages—so features can evolve without tangling concerns.

React

Redux

React Router

CSS Modules

View project

View code

View project

View code

Dictionary web app

Problem: Users need fast definitions, phonetics, and related word context from a single search. Approach: Consumed a dictionary REST API in React with thoughtful loading and empty states, plus responsive typography for readability across breakpoints. Impact: Highlights API integration patterns I use in real investigations: validate inputs, handle errors, and surface clear outcomes.

React

REST API

CSS

View project

View code

View project

View code

Todo app

Problem: Task lists must stay predictable as users add, filter, and reorder items. Approach: Centralized state with Redux and polished motion with Framer Motion—animations reinforce state changes instead of distracting from them. Impact: A compact example of state architecture plus UX details that improve perceived quality and clarity.

React

Redux

Framer Motion

View project

View code