booting qa_automation_engineer.spec.ts …
uday_singh_chauhan.spec.ts
suites: 0/10 passing

QA Automation Engineer / SDET — building test frameworks that catch what manual testing can't, from REST APIs to LLM-powered chatbots.

Engineering Metrics

0
Years Experience
0
Automation Scripts
30–40%
Regression Efficiency
AI/LLM
Quality Engineering

About Me

I'm Uday — a QA engineer based in Delhi who's spent the last four years turning testing into a craft, not just a checklist. I like building automation that other engineers can actually pick up and extend, not scripts that only make sense to the person who wrote them. Lately I've been pulled into a niche most testers haven't touched yet: figuring out how to actually test AI products, where "pass or fail" isn't always obvious. Outside of the day job, I'm the kind of person who reads the whole error log before asking for help — and usually finds the answer in there.

Summary

Results-driven QA Automation Engineer with 4+ years architecting automated test solutions for web applications, REST APIs, and AI/LLM-driven platforms. Specializes in Playwright (TypeScript/JavaScript) and Selenium WebDriver, with a growing niche in LLM and chatbot quality engineering — intent validation, hallucination detection, and guardrail/prompt-injection testing. Designs scalable Page Object Model frameworks, embeds automation into Jenkins CI/CD pipelines, and delivers measurable gains in regression efficiency and coverage.

What I Engineer

UI Automation

Playwright, TypeScript, Page Object Model, fixtures, locators, assertions, cross-browser testing.

API Automation

REST APIs, REST Assured, Postman, JSON validation, authentication, request/response validation.

AI / LLM Quality

Intent validation, hallucination testing, guardrails, prompt injection, safety and context validation.

CI/CD

Jenkins, GitHub Actions, Docker, Maven, parallel execution, automated reporting.

What I Bring

The lens I test through — beyond just running scripts.

Shift-left by default

Automated regression lives inside the CI/CD pipeline from day one, so failures surface in minutes on a build — not days later in a QA queue.

AI-native quality engineering

Actively testing LLM behavior — hallucinations, guardrails, prompt injection — a discipline most teams haven't built a strategy for yet.

Frameworks, not one-off scripts

Page Object Model architecture built to be extended by other engineers, not relearned from scratch on every project.

Quality as a measurable lever

30–40% regression-efficiency gains aren't a side effect — they're the target, tracked and reported like any other engineering metric.

Full-stack coverage, one engineer

UI, API, backend data, and mobile in a single skill set — ground that often needs three specialists to cover.

Fast with new tooling

Already building AI-assisted workflows with Cursor and Copilot — comfortable adopting whatever accelerates the team next.

How I Approach Automation Framework Design

I design around maintainability, reusability, scalability, and reliable feedback — not just scripts that pass today.

Reusability

Avoid duplicating common actions by building reusable page methods, utilities, fixtures, and API helpers.

Separation of Concerns

Test scenarios stay separate from page interactions, test data, API utilities, and configuration.

Maintainability

Tests should stay easy to update when application behavior or UI structure changes.

Scalability

New test scenarios should be addable without unnecessary duplication.

Data Management

Test data and environment-specific configuration stay separated from test logic.

Reliability

Stable locators, explicit synchronization, meaningful assertions, and controlled test isolation.

How I Decide What to Automate

Good candidates

  • Repetitive, stable scenarios
  • Business-critical workflows
  • High regression value
  • API validations
  • Data-driven and negative scenarios

Usually not worth automating

  • Highly unstable / rapidly changing UI
  • One-time exploratory checks
  • Anything requiring subjective human judgment

Live Test Run

Hit run — this is genuinely executing in your browser, not a recording.

0.00s
expect(experience.years).toBeGreaterThanOrEqual(4)
expect(automation.scripts).toBe('30+')
expect(regression.efficiencyGain).toBeWithin('30–40%')
expect(framework.pattern).toBe('Page Object Model')
expect(cicd.tool).toBe('Jenkins')
expect(specialization).toContain('LLM & chatbot QE')

AI / LLM Testing Lab

Simulated examples of checks I run against LLM-powered products — not connected to a production system.

API Testing Playground

Mock demonstration — no real requests are sent, no personal data involved.

/api/users

Click Send Request to see a mock response.

CI/CD Pipeline

Code Push

Feature branch

Playwright Suite

30+ scripts, POM

Jenkins Pipeline

30% faster runs

Regression Report

Auto-flagged failures

Code Push

Feature branch

Playwright Suite

30+ scripts, POM

Jenkins Pipeline

30% faster runs

Regression Report

Auto-flagged failures
Git GitHub GitHub Actions Jenkins Docker Maven BrowserStack

Core Skills

ai / llm quality engineering
Hallucination detection Guardrail testing Prompt-injection testing Intent validation Conversational accuracy testing Chatbot workflow validation
test automation
Playwright (TS/JS) Playwright-Cucumber (BDD) Playwright-Mocha Selenium WebDriver Java TestNG Page Object Model Data-Driven Testing API mocking & network interception
api & backend testing
REST APIs REST Assured Postman GET / POST / PUT / DELETE JSON validation SQL MySQL
mobile testing
Manual iOS testing Manual Android testing Functional validation Compatibility validation
ci/cd & tools
Jenkins GitHub Actions Docker Git GitHub Maven BrowserStack Jira Cursor AI GitHub Copilot
programming & practice
Java JavaScript TypeScript OOP Design Patterns Clean Code STLC Risk-Based Testing RTM Root Cause Analysis

Work Experience

Aug 2025 – PresentRUNNING

SDET — Wyzard.AI

AI company building products that use artificial intelligence to improve user engagement and customer experience.

  • Engineered and maintained 30+ Playwright (TypeScript/JavaScript) automation scripts for AI-driven enterprise applications, expanding coverage and slashing manual regression effort.
  • Architected reusable Playwright components following Page Object Model principles, boosting maintainability and framework scalability.
  • Validated LLM-powered chatbot workflows end-to-end — intent recognition, hallucination detection, conversational accuracy, and guardrail/prompt-injection testing.
  • Drove API validation alongside UI automation, covering request/response verification and backend data checks with REST Assured and Playwright.
  • Used Playwright network interception and API mocking to stress-test app behavior under varied backend response scenarios.
  • Integrated Playwright regression suites into Jenkins CI/CD pipelines, improving regression execution efficiency by 30%.
  • Accelerated automation development using Cursor AI and GitHub Copilot, cutting script authoring and debugging time.
Apr 2024 – Aug 2025PASS

Software Test Engineer — ThrivePass

Technology company building employee benefits platforms that streamline enrollment and engagement.

  • Maintained and executed 50+ automated test cases with Selenium WebDriver, Java, and TestNG, driving a 40% gain in regression execution efficiency.
  • Performed manual mobile testing across iOS and Android, catching platform-specific defects before release.
  • Owned API and backend testing with REST APIs, Postman, SQL, and MySQL across enterprise web applications.
  • Led regression and smoke testing cycles supporting release validation across concurrent feature deployments.
  • Strengthened framework stability by refactoring reusable test components and optimizing execution suites.
  • Managed the full defect lifecycle in Jira, partnering with Agile teams to drive timely resolution.
Sep 2022 – Apr 2024PASS

Software Test Engineer — JDIT Business Solutions

Enterprise software solutions and IT consulting provider.

  • Executed functional, regression, smoke, sanity, and re-testing cycles for enterprise applications.
  • Automated web-based workflows using Selenium WebDriver, Java, and Cucumber.
  • Designed test scenarios and test cases directly from business requirement documents.
  • Managed defect lifecycle in Jira in close collaboration with developers and QA teams.
Jan 2022 – Aug 2022PASS

Software Engineer Trainee — Infogain

Global consulting and technology services company.

  • Performed manual and functional testing, defect tracking, and test case creation.
  • Collaborated within Agile/Scrum teams on issue triage and resolution.
  • Built foundational expertise in STLC, Jira defect management, and QA best practices.

Projects

TC-01

ChatBot SDK — AI agent for visitor engagement

Automated UI testing for AI-powered chatbot workflows using Playwright. Validated chatbot responses, intent detection, visitor interactions, conversational flow, and hallucination scenarios.

TC-02

LinkedIn As Communication Channel

Goal-based communication module for LinkedIn engagement. Tested messaging, follow-up, and engagement workflows across multiple scenarios.

TC-03

Bulk Agentic Mails

AI-driven outbound email campaign feature. Validated AI-driven email workflows, lead tracking, and engagement analytics; tested personalized sequencing and campaign execution.

TC-04

Domain Allocation

Email outreach feature for scalable outbound communication. Tested domain allocation logic, deliverability workflows, and campaign continuity scenarios.

TC-05

Engage

Employee benefits and wellbeing platform. Executed automation and regression testing across platform features; supported defect tracking and release validation in Jira; manual mobile testing on iOS and Android.

TC-06

3E (Protect / News / Exchange)

Environmental health and safety platform. Performed functional, regression, and basic automation testing; maintained test scripts and managed defects using Jira.

TC-07

Santander & Mitchell

Retail banking and car insurance applications. Performed functional, regression, and smoke testing across banking and insurance claims/policy workflows.

Education

B.Tech, Computer Science & Engineering

Manav Rachna International Institute of Research & Studies, Faridabad

2022

Get in touch

Open to QA automation and SDET roles, particularly where AI/LLM quality engineering is part of the brief.