Senior QA Automation Engineer

Crop.photo

IndiaremotePosted 1 month ago

Skill Required

QA-Automation-EngineerSenior-QA-Automation-EngineerAutomation-TestingQuality-Assurance-EngineerSoftware-QA-EngineerAI-TestingSenior-Automation-QA-EngineerSenior-QA-Automation-TesterSenior-Automation-QASenior-QA-AutomationSenior-Automation-Test-EngineerSenior-Quality-Assurance-Automation-SpecialistPrincipal-QA-Automation-EngineerQA EngineerautomationJMeterMachine LearningComputer VisionGitHub ActionsManual TestingSystem DesignGenerative AIPostmanEngineeringR ProgrammingJavaScriptServerlessPlaywrightJenkinsSeleniumbuildingCypressetc.)TestNGPythondesignGitCI/CDCloudFulltime

Key highlights

Required experience: 5-8 years
Key benefit: Flexible work environment / remote arrangements
Notable requirement: Experience validating ML systems or computer vision pipelines
Notable requirement: Proficiency in Java, Python, or JavaScript

Role overview

Evolphin is building the next generation of AI-powered media workflows for enterprise media teams managing large image and video libraries at scale. The platform adds a conversational AI layer for extracting intelligence from media, enabling powerful search, conversational discovery, and automation of media workflows through AskAI. We are looking for a QA Automation Engineer (5–8 years experience) who can take ownership of automation strategy and quality engineering for our AI-powered platform. This role is primarily automation-focused but requires hands-on manual testing for new features, exploratory scenarios, AI output validation, and edge-case workflows to ensure the reliability, usability, performance, and scalability of image and video automation workflows.

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
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
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.)

Requirements

5 to 7 years of hands-on QA automation experience in fast-paced product environments
Web Automation: Deep expertise in Playwright, or Cypress—you know when to use which
API Testing: Proven experience with Postman, Newman, RestAssured, or similar tools
AI/ML Testing: Experience validating machine learning systems or computer vision pipelines
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

Nice to have

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

Benefits

Impact at scale: Build the backbone of a platform trusted by major brands and enterprises to automate critical creative workflows.
Innovation-driven: Collaborate at the intersection of backend, AI, and cloud automation.
Growth opportunities: Lead backend strategy while mentoring and shaping engineering practices.
Flexible work environment: Support for remote arrangements tailored to your needs.
AI-First Product: You're not testing CRUD apps—you're validating cutting-edge computer vision and generative AI workflows that didn't exist three years ago.