About Us
Evolphin is building the next generation of AI-powered media workflows for enterprise media teams managing large image and video libraries at scale, including environments with tens of millions of video assets and extremely large metadata and embedding footprints. Its platform adds a conversational AI layer for extracting intelligence from media, enabling powerful search, conversational discovery, and automation of media workflows through AskAI.
We're now pushing further into AI — building the next generation of intelligent, automation-first media management — and we're looking for people who want to help build that future from the ground up.
Role Overview
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 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.
Key Responsibilities
- Design and own the end-to-end automation framework for web, API, and AI-driven featuresBuild API automation suites for our core automation workflows and integrations (Postman/Newman/RestAssured)Drive UI automation using Selenium, Playwright, or CypressEnsure cross-browser compatibility for our design-heavy, canvas-based interfacesBuild performance testing suites to validate image/video processing throughput under loadEmbed quality gates into our deployment pipelines (GitHub Actions/Jenkins)Enable rapid, confident releases through automated testing at every stageCreate validation frameworks for non-deterministic ML results—balancing precision with creative flexibilityPartner with Product to define acceptance criteria for AI-driven featuresWork alongside Engineering to shift-left quality and build testability into system designExperience using LLMs (ChatGPT, GitHub Copilot, Cursor, etc.) to generate and refactor automation scriptsAbility to review, validate, and harden AI-generated test code (not blindly accept output)Experience building prompt templates for test case generation from user storiesFamiliarity with AI-assisted test case generation and coverage analysisUnderstanding of how to test AI-driven features (prompt testing, hallucination detection, cost optimizations, response validation)Ability to design deterministic validation strategies for probabilistic AI outputsExperience integrating automation into AI-heavy workflows (semantic search, generative features, etc.)
- 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.)
