With the goal of expanding our team to 150–200 employees in 2027, Trivita AI is looking for talented individuals to join us in our next phase of growth.
Trivita AI is hiring Junior and Middle Automation QA/QC Engineers for web, mobile, API testing, test automation, and AI quality evaluation.
Trivita AI builds AI-powered products and platforms for businesses, including AI assistants, workflow automation agents, knowledge search, and speech recognition.
As a Middle/Junior Automation QA/QC Engineer, you will ensure product quality across web, mobile, desktop, APIs, and AI features. The role focuses on three areas: risk-based compatibility testing across real-world devices and platforms, test automation, and AI quality evaluation through golden datasets, data labeling, and model version comparisons.
Job description
Test analysis and design
- Analyze user stories and business requirements, identify gaps, inconsistencies, and ambiguities, and propose testable acceptance criteria.
- Design test cases and scenarios using standard techniques such as Equivalence Partitioning, Boundary Value Analysis, Decision Tables, and State Transitions.
- Apply end-to-end testing principles across UI, API, backend, and database layers, assessing the impact of changes on related workflows.
- Build and maintain compatibility testing matrices based on real usage data, device market share, operating systems, browsers, and screen sizes.
Cross-platform testing and automation
- Perform functional and regression testing for web, mobile, and API applications.
- Develop automated E2E tests across Chrome, Edge, Firefox, and Safari using Playwright, Cypress, or Selenium, including verification on real Safari environments.
- Test iOS and Android applications using physical devices, emulators/simulators, and device farms with Appium, Flutter integration_test, or Patrol.
- Validate mobile features such as permissions, camera, microphone, push notifications, deep links, biometrics, app upgrades, and offline behavior.
- Test localization, Vietnamese text rendering, input methods, date and number formats, and compatibility across Windows, macOS, and Linux.
- Perform API testing using Postman, Swagger/OpenAPI, or pytest, including schema validation, HTTP status codes, SQL checks, and service mocking.
- Integrate automated tests into CI/CD pipelines, manage flaky tests, automate repetitive tasks, and support load testing.
AI quality evaluation
- Build and maintain test sets and golden datasets for AI model evaluation.
- Perform data labeling and review according to labeling guidelines, ensuring accuracy and consistency.
- Evaluate AI outputs using metrics and quality rubrics, including WER/CER for speech-to-text and response quality assessment for chatbots.
- Test multi-step AI agents for issues such as incorrect tool selection, execution order errors, infinite loops, hallucinations, and basic prompt injection.
- Analyze failure cases, identify error patterns, and provide feedback to AI engineers.
- Retest models and engines after releases and compare results across versions to detect quality regressions.
Quality management and collaboration
- Document clear, reproducible bugs with supporting evidence and track them to resolution in Jira.
- Monitor quality indicators such as defect leakage and automation coverage.
- Participate in Scrum ceremonies, estimate assigned tasks, and collaborate with developers, product managers, and AI engineers.
- Maintain accurate test results, bug logs, datasets, and test cases while contributing to continuous QA process improvement.
Requirements
Experience and core skills
- Junior: 6 months to 2 years of software testing experience.
- Middle: 3+ years of software testing experience, including at least 2 years developing automated tests.
- Solid understanding of STLC, bug life cycle, test types, test levels, and test design techniques.
- Strong systems thinking and the ability to assess the impact of changes across end-to-end workflows.
- Experience with API testing using Postman or Swagger, including JSON, HTTP methods, status codes, and basic SQL.
- Experience testing iOS and Android applications using real devices, emulators/simulators, and debugging tools.
- Basic understanding of AI model evaluation, multi-step AI agent testing, and common agent failure patterns.
- Experience with AI data labeling or evaluation, or the ability to learn quickly.
- Familiarity with Git and Docker, and the ability to read English technical documentation.
- Proficiency in AI coding assistants and prompt engineering for generating test cases, writing automation scripts, debugging, and improving productivity while validating AI outputs and complying with data security policies.
Level-specific technical requirements
Junior
- Basic programming skills in Python or JavaScript/TypeScript.
- Ability to write simple scripts using pytest or requests for batch API calls and metric calculation.
- Ability to perform functional, regression, and compatibility testing across defined device matrices.
- Ability to label and review AI datasets and report reproducible bugs with supporting logs.
Middle
- Proficiency in at least one web E2E automation tool, such as Playwright, Cypress, or Selenium.
- Experience developing automation frameworks using Page Objects, fixtures, and stable locators.
- Experience integrating automated tests into CI/CD pipelines, enabling parallel execution, and managing flaky tests.
- Basic Kubernetes knowledge, including using kubectl to inspect logs and test environments.
- Ability to design AI evaluation sets, quality rubrics, and labeling guidelines while mentoring Junior engineers.
Technology stack
- Web Automation: Playwright, Cypress, Selenium.
- Mobile Testing: Appium, Flutter integration_test, Patrol, BrowserStack, LambdaTest.
- API Testing: pytest, requests, Postman, Newman, Swagger/OpenAPI, WireMock.
- Performance Testing: k6, Locust.
- AI Evaluation: Label Studio, promptfoo, DeepEval.
- Infrastructure & CI/CD: Git, Docker, Kubernetes, GitHub Actions, GitLab CI.
- QA Management: Jira, Allure.
First 6 months expectations
- Automate critical user flows across the agreed browser and device compatibility matrix, with tests executed for every release candidate.
- Maintain a golden dataset and evaluation rubric for at least one AI feature, comparing results after each model or engine release.
- Track flaky test rates and keep them below the agreed threshold, such as 2%.
Preferred qualifications
- Experience testing speech-to-text products or using data labeling tools such as Label Studio or CVAT.
- Experience evaluating LLMs using promptfoo, DeepEval, Ragas, or equivalent tools.
- Familiarity with device farms such as BrowserStack, LambdaTest, Sauce Labs, or Firebase Test Lab.
- Experience with visual regression testing and accessibility testing based on WCAG 2.2.
- Basic security testing knowledge, including OWASP Top 10 or OWASP MASVS.
- Experience profiling mobile performance using Android Studio Profiler or Xcode Instruments.
- Experience working in Scrum or Agile environments.
- ISTQB Foundation certification.
Contact information
- Address: No. 01, Street 104, Quarter 3, Binh Trung Ward, Ho Chi Minh City
- Phone: 0937519182
- Email: hr@trivita.ai / le.vu@trivita.ai
