高级 QA 自动化工程师
Senior QA Automation Engineer
关于我们
Evolphin 正在为管理大规模图像和视频库的企业媒体团队打造下一代 AI 驱动的媒体工作流程，包括包含数千万视频资产以及极其庞大的元数据和嵌入式足迹的环境。其平台为从媒体中提取智能信息添加了对话式 AI 层，通过 AskAI 实现强大的搜索、对话式发现和媒体工作流程自动化。
我们现在进一步深入 AI —— 构建下一代智能、以自动化为核心的媒体管理 —— 我们正在寻找希望从零开始构建未来的人才。
职位概述
我们正在寻找一位 QA 自动化工程师（5–8 年经验），能够负责我们 AI 驱动平台的自动化策略和质量工程。
该职位主要以自动化为主，但也需要对新功能、探索性场景、AI 输出验证和边缘情况工作流进行手动测试。你将在确保我们的图像和视频自动化工作流程的可靠性、可用性、性能和可扩展性方面发挥关键作用。
该职位适合在快节奏的初创环境中茁壮成长，并享受构建自动化框架，同时在需要时通过手动验证贴近产品行为的人。
主要职责
· 设计并主导针对网页、API 和 AI 驱动功能的端到端自动化框架
- 为我们的核心自动化工作流程和集成构建 API 自动化套件（Postman/Newman/RestAssured）
- 使用 Selenium、Playwright 或 Cypress 推动 UI 自动化
- 确保我们设计密集型、基于画布的界面的跨浏览器兼容性
- 构建性能测试套件，以验证负载下的图像/视频处理吞吐量
- 将质量门控嵌入到我们的部署流水线（GitHub Actions/Jenkins）
- 通过每个阶段的自动化测试实现快速、自信的发布
- 为非确定性 ML 结果构建验证框架 —— 在精度与创意灵活性之间取得平衡
- 与产品团队合作，为 AI 驱动功能定义验收标准
- 与工程团队协作，推动质量左移，并在系统设计中构建可测试性
- 使用 LLM（ChatGPT、GitHub Copilot、Cursor 等）生成和重构自动化脚本
- 能够审查、验证并强化 AI 生成的测试代码（不盲目接受输出）
- 构建提示模板的经验
查看英文原文
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 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
Good 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.
Originally posted on Himalayas