QA Automation Engineer

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 behavior through manual validation when needed.

• 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 
• 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
• Experience using LLMs (ChatGPT, GitHub Copilot, Cursor, etc.) to generate and refactor automation scripts
• Ability to review, validate, and harden AI-generated test code (not blindly accept output)
• Experience building prompt templates for test case generation from user stories
• Familiarity with AI-assisted test case generation and coverage analysis
• Understanding of how to test AI-driven features (prompt testing, hallucination detection, cost optimizations, response validation)
• Ability to design deterministic validation strategies for probabilistic AI outputs
• Experience integrating automation into AI-heavy workflows (semantic search, generative features, etc.).

• 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

• 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

• 🎯 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.