QA Automation Engineer at Crop.photo

, , India -

Full Time

Start Date

Immediate

Expiry Date

24 May, 26

Salary

0.0

Posted On

23 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Automation Strategy, Manual Testing, Web Automation, API Automation, UI Automation, Selenium, Playwright, Cypress, Postman, Newman, RestAssured, Performance Testing, CI/CD, GitHub Actions, Jenkins, AI Output Validation

Industry

technology;Information and Internet

Description

We are looking for a QA Automation Engineer (4–7 years experience) who can take ownership of automation strategy and quality engineering for our AI-powered platform. This role is primarily automation-focused, but will also require hands-on manual testing for new features, exploratory scenarios, AI output validation, and edge-case workflows. You will play a critical role in ensuring the reliability, usability, performance, and scalability of our image and video automation workflows. This role is ideal for someone who thrives in fast-moving startup environments and enjoys building automation frameworks while staying close to product behaviour through manual validation when needed. Key Responsibilities Design and own the end-to-end automation framework for web, API, and AI-driven features Build API automation suites for our core automation workflows and integrations (Postman/Newman/RestAssured) Drive UI automation using Selenium, Playwright, or Cypress for our creative studio and dashboard Validate complex workflow automation chains (image ingestion → AI processing → asset delivery) Ensure cross-browser compatibility for our design-heavy, canvas-based interfaces Build performance testing suites to validate image/video processing throughput under load Embed quality gates into our deployment pipelines (GitHub Actions/Jenkins) Enable rapid, confident releases through automated testing at every stage Develop testing strategies for AI-generated outputs (image crops, background removal, resolution enhancement) Create validation frameworks for non-deterministic ML results—balancing precision with creative flexibility Partner with Product to define acceptance criteria for AI-driven features Work alongside Engineering to shift-left quality and build testability into system design 4–7 years of hands-on QA automation experience in fast-paced product environments Web Automation: Deep expertise in Selenium, Playwright, or Cypress—you know when to use which API Testing: Proven experience with Postman, Newman, RestAssured, or similar tools Programming: Proficiency in Java, Python, or JavaScript—you can read and write production code CI/CD: Experience integrating tests into GitHub Actions, Jenkins, or similar pipelines SaaS Domain: Track record testing cloud-based, multi-tenant products at scale Startup DNA: Comfortable with ambiguity, rapid iteration, and wearing multiple hats Good to Have AI/ML Testing: Experience validating machine learning systems or computer vision pipelines Visual Domain: Background in image/video processing, creative tools, or digital asset management Performance Engineering: Hands-on with JMeter, k6, or Gatling for load testing Cloud Platforms: AWS or GCP experience, particularly with serverless or containerized architectures What We're Looking For 🎯 Ownership Mentality: You don't wait for tickets—you identify gaps, propose solutions, and ship. You treat test infrastructure as a product, not an afterthought. 🏗 Builder's Mindset: You've built automation frameworks from scratch before. You understand that in a startup, "done" beats "perfect," but "reliable" beats "done." ⚡Startup Agility: You thrive in environments where priorities shift, features evolve weekly, and the codebase grows fast. You're energized by high-velocity shipping, not slowed by it. 🗣️ Communication Excellence: You translate technical risks into business impact. You can explain to a designer why their AI crop feature failed validation, and to leadership why a release needs to hold.

Responsibilities

The role involves designing and owning the end-to-end automation framework for web, API, and AI-driven features, alongside building API and UI automation suites. Key duties also include embedding quality gates into deployment pipelines and developing testing strategies for AI-generated outputs.