7 Playwright Portfolio Projects That Get You Hired (2026)

You have completed a Playwright course. You have earned a certificate. You have even passed an interview prep quiz. But when the hiring manager opens your GitHub profile and sees empty repositories or forked demo code, the conversation ends before it starts.

In 2026, the QA automation job market is competitive. Companies posting Playwright jobs receive hundreds of applications. The candidates who get callbacks are not the ones with the longest resumes — they are the ones with the most convincing proof of skill. That proof lives in your portfolio.

This guide gives you 7 complete project ideas, each targeting a different skill that hiring managers actively look for. Build three of them well, and you will stand out from 90% of applicants. Build all seven, and you will have a portfolio that speaks louder than any certification. For the skills you should highlight, see our Playwright skills for resume guide.

Why a Playwright Portfolio Gets You Hired

Let's be direct about what happens during a typical hiring process for a QA automation role. The recruiter screens resumes for keywords — Playwright, TypeScript, CI/CD, API testing. That takes seconds. But the technical interviewer does something different. They open your GitHub.

Here is what they look for in the first 60 seconds:

• Commit history — Are you actively writing code, or did you push everything in one commit six months ago?
• README quality — Can they understand what the project does without cloning it?
• Test structure — Do you use Page Object Model? Are tests organized by feature?
• CI/CD integration — Is there a GitHub Actions workflow? Does it actually pass?
• Variety — Do you only write login tests, or can you handle APIs, visual regression, and accessibility?

A strong portfolio answers every one of these questions before the interview even begins. It shifts the conversation from "Can you do this?" to "Tell me more about how you did this." That is a fundamentally different interview, and it is one you are far more likely to win.

The salary data for 2026 shows that Playwright automation engineers with demonstrable project experience command 15–25% higher starting offers than those with only certifications. Your portfolio is not just a nice-to-have — it is a salary negotiation tool.

Project 1: E-Commerce End-to-End Test Suite

What it proves: You can test a real application from start to finish — the single most common task in any QA automation role.

Every e-commerce application follows a predictable flow: browse products, search, filter, add to cart, update quantities, proceed to checkout, fill shipping and payment forms, and confirm the order. Your test suite should cover this entire journey, including the edge cases that break in production.

Target Application

Use a publicly available demo app like Sauce Demo (saucedemo.com), Automation Exercise, or DemoBlaze. These are stable, well-known in the QA community, and hiring managers recognize them instantly.

What to Cover

• Product search and filtering — verify search results match queries, sort by price/name works correctly
• Cart management — add items, remove items, update quantities, verify totals
• Checkout flow — complete a purchase with valid data, verify confirmation page
• Negative testing — invalid credit card, empty cart checkout, expired session handling
• Authentication — login, logout, locked-out user, invalid credentials

import { test, expect } from '@playwright/test';
import { ProductPage } from '../pages/product.page';
import { CartPage } from '../pages/cart.page';
import { CheckoutPage } from '../pages/checkout.page';

test.describe('Checkout Flow', () => {
  let productPage: ProductPage;
  let cartPage: CartPage;
  let checkoutPage: CheckoutPage;

  test.beforeEach(async ({ page }) => {
    productPage = new ProductPage(page);
    cartPage = new CartPage(page);
    checkoutPage = new CheckoutPage(page);
    await productPage.goto();
  });

  test('complete purchase with valid payment', async () => {
    await productPage.addToCart('Sauce Labs Backpack');
    await productPage.addToCart('Sauce Labs Bike Light');
    await cartPage.open();
    await expect(cartPage.items).toHaveCount(2);
    await cartPage.checkout();
    await checkoutPage.fillShipping({
      firstName: 'Jane',
      lastName: 'Doe',
      zip: '90210'
    });
    await checkoutPage.confirmOrder();
    await expect(checkoutPage.successMessage)
      .toContainText('Thank you for your order');
  });

  test('cannot checkout with empty cart', async () => {
    await cartPage.open();
    await expect(cartPage.checkoutButton).toBeDisabled();
  });
});

Why Hiring Managers Love This

E-commerce testing is the bread and butter of most QA teams. If you can test a shopping flow cleanly — with Page Object Model, meaningful assertions, and proper test isolation — you have proven you can handle the most common automation work on day one. Check out our real-time Playwright projects guide for more application ideas.

Project 2: API + UI Integration Tests

What it proves: You understand that modern applications are not just a UI — they are a UI sitting on top of APIs, and testing both layers together catches bugs that either layer alone would miss.

Most QA automation engineers test the UI or the API, but rarely both in the same test suite. Combining them is a significant differentiator. It shows you think about the system as a whole, not just the screen in front of you.

The Approach

Use Playwright's built-in request context to make API calls alongside browser interactions. The pattern is straightforward: create test data via API, verify it appears in the UI, modify it through the UI, then verify the change via API.

import { test, expect } from '@playwright/test';

test('API-created product appears in UI search', async ({ page, request }) => {
  // Create product via API
  const response = await request.post('/api/products', {
    data: {
      name: 'Playwright Test Widget',
      price: 29.99,
      category: 'automation'
    }
  });
  await expect(response).toBeOK();
  const product = await response.json();

  // Verify product appears in UI
  await page.goto('/products');
  await page.getByPlaceholder('Search products')
    .fill('Playwright Test Widget');
  await page.getByRole('button', { name: 'Search' }).click();
  await expect(page.getByText('Playwright Test Widget'))
    .toBeVisible();
  await expect(page.getByText('$29.99')).toBeVisible();

  // Cleanup via API
  await request.delete(`/api/products/${product.id}`);
});

Key Tests to Include

• Data consistency — Create via API, verify in UI. Create via UI, verify via API.
• Authentication tokens — Login via API to skip UI login, then perform UI tests (speeds up test execution significantly)
• Error handling — What happens in the UI when the API returns a 500? Use page.route() to mock API failures
• Pagination and filtering — Create 50 items via API, then verify the UI paginates correctly

For a deeper dive into API testing patterns, see our Playwright API testing guide.

Project 3: CI/CD Pipeline with GitHub Actions

What it proves: You do not just write tests — you ship them. You understand that tests without automation are just scripts sitting on a laptop.

This is the project that separates hobbyists from professionals. A complete CI/CD pipeline shows that you understand the full lifecycle of test automation: write, run, report, and notify. Every company running Playwright in production has a pipeline, and they need engineers who can build and maintain one.

Pipeline Architecture

1. Trigger — Run on push to main, on pull requests, and on a daily schedule
2. Setup — Install dependencies, cache node_modules and Playwright browsers
3. Lint — Run ESLint on test code to enforce standards
4. Test — Execute Playwright tests across Chromium, Firefox, and WebKit
5. Report — Generate HTML report and upload as artifact
6. Notify — Send Slack notification with pass/fail summary

name: Playwright Tests
on:
  push:
    branches: [main]
  pull_request:
    branches: [main]
  schedule:
    - cron: '0 6 * * *'  # Daily at 6 AM UTC

jobs:
  test:
    runs-on: ubuntu-latest
    strategy:
      matrix:
        project: [chromium, firefox, webkit]
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-node@v4
        with:
          node-version: 20
          cache: 'npm'
      - run: npm ci
      - run: npx playwright install --with-deps ${{ matrix.project }}
      - run: npx playwright test --project=${{ matrix.project }}
      - uses: actions/upload-artifact@v4
        if: always()
        with:
          name: report-${{ matrix.project }}
          path: playwright-report/
      - name: Slack Notification
        if: failure()
        uses: 8398a7/action-slack@v3
        with:
          status: ${{ job.status }}
          fields: repo,message,commit,author
        env:
          SLACK_WEBHOOK_URL: ${{ secrets.SLACK_WEBHOOK }}

For the complete setup walkthrough, see our Playwright GitHub Actions CI/CD tutorial.

Project 4: AI-Generated Test Suite with Claude MCP

What it proves: You are not just keeping up with the industry — you are ahead of it. AI-assisted testing is the single hottest skill in QA automation in 2026, and having a project that demonstrates it will make your portfolio unforgettable.

This project uses Claude AI with the Playwright MCP (Model Context Protocol) server to generate test scripts from plain-English user stories. It is the project that makes interviewers say, "Wait, show me how that works."

The Workflow

1. Write user stories in a stories/ directory as plain text or markdown files
2. Connect Claude Code to your project with the Playwright MCP server installed
3. Generate tests by feeding user stories to Claude and letting it browse your app to create accurate selectors
4. Review and refine the generated tests, adding edge cases Claude may have missed
5. Track generation metadata — include comments noting which tests were AI-generated vs. hand-written

Project Structure

• stories/ — User stories in markdown format
• tests/ai-generated/ — Tests generated by Claude MCP
• tests/manual/ — Hand-written tests for comparison
• reports/ — Coverage comparison between AI and manual tests
• README.md — Detailed explanation of the AI workflow, including prompt examples

The key to making this project impressive is documentation. Include screenshots of the Claude MCP conversation, show before/after comparisons of AI-generated vs. hand-written tests, and document the time savings. Hiring managers want to know: does this actually work, and can you use it responsibly?

Project 5: Visual Regression Testing Dashboard

What it proves: You catch bugs that functional tests miss. Visual regression testing detects layout shifts, font changes, color mismatches, and responsive breakpoint failures — the kind of bugs that slip through traditional assertion-based testing.

This project uses Playwright's built-in screenshot comparison to capture baseline images and detect visual differences on every test run. You can extend it with Percy or a custom dashboard that displays diffs side by side.

What to Test

• Full-page screenshots across desktop, tablet, and mobile viewports
• Component-level screenshots for headers, footers, navigation, cards, and forms
• Dark mode vs. light mode comparisons
• Before/after deployment visual diffs
• Cross-browser visual consistency between Chromium, Firefox, and WebKit

import { test, expect } from '@playwright/test';

const viewports = [
  { name: 'desktop', width: 1280, height: 720 },
  { name: 'tablet',  width: 768,  height: 1024 },
  { name: 'mobile',  width: 375,  height: 812 },
];

for (const vp of viewports) {
  test(`homepage visual - ${vp.name}`, async ({ page }) => {
    await page.setViewportSize({
      width: vp.width,
      height: vp.height
    });
    await page.goto('/');
    // Wait for animations and lazy images to settle
    await page.waitForLoadState('networkidle');
    await expect(page).toHaveScreenshot(
      `homepage-${vp.name}.png`,
      { maxDiffPixelRatio: 0.01 }
    );
  });
}

For the complete visual testing methodology, check our Playwright visual regression testing guide.

Making It Portfolio-Worthy

Go beyond basic screenshots. Create a simple HTML report that displays baseline, current, and diff images side by side. Include a summary table showing which pages passed, which failed, and the percentage of pixel difference. Store baseline images in your repo so reviewers can see the actual comparisons.

Project 6: Accessibility Audit Automation

What it proves: You care about quality beyond functional correctness. Accessibility testing is increasingly mandatory — legally and ethically — and companies actively seek engineers who can automate WCAG compliance checks.

This project integrates axe-core with Playwright to scan pages for accessibility violations, generate detailed reports, and track compliance over time. It is the project that shows you think about all users, not just the happy path.

What to Automate

• WCAG 2.1 AA compliance scans on every page of your target application
• Keyboard navigation tests — can users tab through forms, activate buttons, navigate menus without a mouse?
• Color contrast validation for text, buttons, and interactive elements
• ARIA label verification — do images have alt text? Do form inputs have labels?
• Screen reader compatibility — verify landmark regions, heading hierarchy, and live region announcements

import { test, expect } from '@playwright/test';
import AxeBuilder from '@axe-core/playwright';

const pages = ['/', '/products', '/cart', '/checkout', '/contact'];

for (const url of pages) {
  test(`a11y audit: ${url}`, async ({ page }) => {
    await page.goto(url);
    const results = await new AxeBuilder({ page })
      .withTags(['wcag2a', 'wcag2aa', 'wcag21aa'])
      .analyze();

    // Log violations for debugging
    if (results.violations.length > 0) {
      console.log(`Violations on ${url}:`);
      results.violations.forEach(v => {
        console.log(`  [${v.impact}] ${v.id}: ${v.description}`);
      });
    }

    expect(results.violations).toEqual([]);
  });

  test(`keyboard nav: ${url}`, async ({ page }) => {
    await page.goto(url);
    // Tab through all interactive elements
    const focusable = page.locator(
      'a[href], button, input, select, textarea, [tabindex]:not([tabindex="-1"])'
    );
    const count = await focusable.count();
    for (let i = 0; i < count; i++) {
      await page.keyboard.press('Tab');
      const focused = page.locator(':focus');
      await expect(focused).toBeVisible();
    }
  });
}

For a comprehensive accessibility testing strategy, read our Playwright accessibility testing guide.

Project 7: Cross-Browser Performance Monitor

What it proves: You understand that tests are not just about correctness — they are about performance. A test that passes in 2 seconds on Chromium but takes 15 seconds on WebKit reveals a real problem, and you are the engineer who catches it.

This project runs your test suite across all three Playwright browser engines (Chromium, Firefox, WebKit), measures load times and interaction latency, and generates a comparison report. It is a project that demonstrates depth — the kind of depth that gets you senior-level consideration.

What to Measure

• Page load time (DOMContentLoaded, Load, First Contentful Paint) per browser
• Time to Interactive for key pages
• Test execution duration per browser — which tests are slowest where?
• Network request count and size per page load
• JavaScript error tracking across browsers — catch browser-specific console errors

Implementation Approach

Use Playwright's page.on('console') to capture JS errors, page.evaluate() to read performance.timing data, and the built-in --project flag to run across all browsers. Store results in JSON, then generate a simple HTML comparison dashboard.

Include threshold assertions: if a page takes more than 3 seconds to load in any browser, the test fails. This turns your monitoring project into a performance gate that teams can drop directly into their CI/CD pipeline.

Pair this with the CI/CD pipeline from Project 3, and you have a complete automated performance monitoring system. The combination of Projects 1, 3, and 7 alone would make a compelling portfolio for most mid-level QA roles.

How to Showcase Your Portfolio

Building the projects is half the work. Presenting them properly is the other half. A brilliant test suite buried in a repo with no README is invisible to hiring managers. Here is how to make your portfolio impossible to ignore.

GitHub README Template

Every project should have a README with these sections:

1. Project title and one-line description — What does this project test?
2. Tech stack badges — Playwright, TypeScript, GitHub Actions, axe-core, etc.
3. Architecture overview — A simple diagram or bullet list showing folder structure and design patterns used
4. Setup instructions — Clone, install, run. It should work in 3 commands or fewer.
5. Test coverage summary — How many tests, what do they cover, what is the pass rate?
6. CI/CD status badge — Green means working. It is the first thing people see.
7. Sample test output — A screenshot or GIF of a test running
8. What I learned — A brief section explaining key decisions and trade-offs

LinkedIn Strategy

Do not just link to your GitHub. Write a short post for each project you complete. Explain the problem it solves, show a code snippet or screenshot, and end with what you learned. Tag it with #PlaywrightTesting, #QAAutomation, and #TestAutomation. Hiring managers and recruiters search these hashtags actively.

Interview Preparation

For each project, prepare answers to these questions:

• "Why did you choose this architecture?" (Page Object Model, fixtures, custom reporters)
• "What was the hardest bug to find?" (Flaky tests, timing issues, cross-browser inconsistencies)
• "How would you scale this?" (Parallel execution, sharding, Docker containers)
• "What would you do differently?" (Shows self-awareness and growth mindset)

For more interview preparation, see our Playwright interview questions guide.

Frequently Asked Questions

Meet Your Instructor

Asim Noaman

Senior QA Automation Engineer & AI Testing Specialist

With years of hands-on experience building test automation frameworks for production applications, Asim specializes in combining traditional QA methodologies with cutting-edge AI tools. He has helped teams adopt Playwright and AI-driven testing workflows to ship faster with fewer bugs.

Udemy Instructor Published course author

Playwright + AI Expert Specialized in AI-powered QA

Production Experience Enterprise-grade frameworks

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