Curriculum Vitae
Yanqing Li
Senior Test Development EngineerAI Testing and Quality Platform
- AI product quality
- Automation and continuous monitoring
- Quality platform and engineering governance
- LocationBeijing, China
- Emaillyqgmail@gmail.com
- GitHubgithub.com/qingye-lab
- Siteyanqing.li
Summary
Profile
14 years in testing, test development and quality engineering; currently a senior test development engineer at Autohome (汽车之家). I own quality assurance for AI marketing, livestreaming and auto-reply, the car marketplace, and multi-platform products, lead a testing team of about 5, and work with roughly 20 engineers, product and business colleagues to move delivery forward.
I build and maintain 100+ UI automation cases and dozens of API cases, reaching 90%+ automation coverage of core business within my scope. API regression runs in CI/CD and has caught real problems at build time. PulseGuard, which I wrote, is used across several company projects for front-end page and API health checks.
I work end to end: from a business problem and a test strategy through platform design, front-end and back-end implementation, deployment and verification. I keep developing CaseFlux, and have open-sourced the AI Playwright Framework, Rootloom and Hengmu, focused on automation execution reliability, failure diagnosis and agent engineering governance.
- Years in testing and quality engineering
- 14 years
- UI automation cases
- 100+
- Automation coverage of core business within my scope
- 90%+
- Current testing team
- about 5
Definitions and scope of these numbers are in the profile above.
Experience
Experience
- 2024.12 — Present
Autohome (汽车之家)
Senior Test Development Engineer
- Own quality assurance for AI marketing tools, the Douyin livestreaming assistant, direct-message and danmaku auto-reply, the car marketplace, H5, mini-program and back-office systems, covering functional, API, UI, exception-path, risk-control and stability verification.
- Lead a testing team of about 5, running requirements review, test planning, task breakdown and release gating, and working with roughly 20 engineering, product and business colleagues to close out quality risks and defects.
- Built and maintain 100+ UI automation cases and dozens of API cases, reaching 90%+ automation coverage of core business within my scope; API regression runs in CI/CD and has caught problems at build time.
- Built PulseGuard myself and applied it across several company projects for front-end page and API health checks, folding scheduled checks, health state, failure evidence and alerts into daily quality work.
- 2021.02 — 2024.08
Lanhu (蓝湖)
Test Development Engineer / Test Lead
- Owned quality assurance for the Lanhu WebApp, its plugins and related collaboration products, covering requirements review, functional and API testing, UI automation, regression verification and pre-release quality checks.
- Took on test task breakdown, release cadence and cross-role quality collaboration, tracking quality risks and defects to closure and improving quality visibility through continuous delivery.
- Drove API and UI automation, multi-environment execution, test data, execution reports and scheduled production monitoring, giving core regression and release verification a stable foundation.
- 2017.11 — 2021.01
MockingBot (墨刀)
Test Engineer / Test Development Engineer
- Tested MockingBot Web, the desktop client, the mobile app, H5 and the Sketch plugin, taking part in requirements review, case design, functional verification, compatibility testing and regression testing.
- Drove API and UI automation into place and took part in building test standards, test tooling and pre-release quality checks, supporting stable delivery of the prototyping and collaboration product.
- 2012.04 — 2017.10
Earlier career
Test EngineerRenren, Lashou, Daojia, Shouqi
- Career timeline: Renren (人人网, 2012.04 - 2014.02), Lashou (拉手网, 2014.04 - 2016.02), Daojia (到家美食会, 2016.03 - 2016.12), Shouqi (首汽约车, 2016.12 - 2017.10).
- Covered clients, business systems, API testing, regression testing, channel package verification and release quality assurance, building a quality foundation across product shapes and business scenarios.
Projects
Selected projects
PulseGuard is in use across several company projects for front-end page and API health checks. CaseFlux is a personal project I keep developing and can demonstrate in an interview; the open-source projects can be examined further through their code, documentation and release history.
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PulseGuard(opens in a new window) UI/API health checks and quality monitoring
- Built independently and now used across several company projects for front-end page and API health checks, covering the React / TypeScript front end, a FastAPI / SQLite back end and Docker deployment, with tasks, health state, failure evidence and alerts managed in one place.
- Designed the health state machine to tell a target failure apart from a broken browser or node, keeping screenshots, response bodies and optional traces, with cooldown and recovery notifications, so a failure can be diagnosed.
- Implemented outbound-only Relay nodes, a shared project script library and a read-only MCP diagnosis entry point; a run and its retries bind to the script source snapshot, so a configuration change cannot alter execution already in flight.
-
CaseFlux AI-native test automation platform
- Building the testing loop around requirements, functional cases, UI automation, real execution and failure diagnosis, owning the product design, domain model, front and back ends, browser extension and execution pipeline.
- Using React, FastAPI, PostgreSQL, Redis, LangGraph and Playwright to accumulate versioned test assets, plan execution records, step results, screenshots and traces.
- Separating case generation, single-run debugging and formal regression; repair suggestions link to execution evidence, changes to high-impact assets are verified and approved, and failure diagnoses and decisions are recorded.
-
AI Playwright Framework(opens in a new window) UI automation framework
- Built on Playwright, pytest and YAML, separating cases, data, elements and shared steps, supporting multiple projects and environments, dynamic collection and CI regression.
- Keeping execution deterministic while adding AI case generation, locator recovery and natural-language task execution per scenario; generated YAML assets are verified in a real browser before they count.
- Constraining framework quality with schema validation, contract tests, duplicate-definition checks and package installation checks, and diagnosing failures from screenshots, logs and Allure reports.
-
Rootloom(opens in a new window) Engineering workflow for coding agents
- Designed the risk routing, root-cause verification, change-scope control and proportional verification flow, so a coding agent implements and reviews changes against repository facts.
- Ships an installable plugin, contract checks and CI; an optional evidence mode links the repository state before and after a change to actual execution results, making completion claims and residual risk reviewable.
-
Hengmu 衡木(opens in a new window) Architecture review and technical decisions
- Connects architecture review, independent verification, option comparison and a change plan; it can also work from design goals and constraints to a target architecture covering data ownership, interfaces and runtime boundaries.
- Validates decision artefacts with Python, JSON Schema, Git evidence and deterministic gates, covering reviews of single repositories, AI agents, mobile clients and multi-project dependencies.
-
Design Skill Arena(opens in a new window) A gallery comparing AI front-end results
- Takes one product brief and collects independently built front-end pages from several models and Skill Chains, keeping the real implementation, screenshots and design sources so responsive behaviour, interaction and visual quality can be compared directly.
- Delivered with Next.js, TypeScript and Cloudflare Pages / R2; the observations are presented as work and method notes rather than dressed up as a ranking of model capability.
Capabilities
Strengths
-
Business quality and delivery
Requirements review, test strategy, release gating and defect retrospectives, covering the exception paths and quality risks in AI marketing, auto-reply and multi-platform products.
-
Automation and continuous monitoring
Built Playwright / pytest automation, API regression and CI gates, and put my own PulseGuard to work on front-end page and API health checks across several company projects.
-
Quality platform engineering
Built the whole thing myself — requirements modelling, a React front end, a Python / FastAPI back end, execution nodes and Docker deployment — turning scattered scripts into reusable, traceable test assets.
-
AI testing and agent practice
Working in CaseFlux and the AI Playwright Framework on natural-language cases, real browser execution, failure diagnosis and repair review, with attention to generation quality, assertions and execution evidence.
-
Engineering review and technical decisions
Using Rootloom and Hengmu to practise risk grading, root-cause verification, architecture review, option trade-offs and deterministic quality gates, so engineering conclusions rest on real verification.
- Requirements
- Functional test cases
- UI automation
- Real execution
- Failure diagnosis
- Reviewed self-healing repair
Skills
Stack
- Test development
- Python
- Playwright
- pytest
- UI
- API automation
- E2E
- YAML
- Allure
- test data
- Platform engineering
- FastAPI
- PostgreSQL
- SQLite
- Redis
- React
- TypeScript
- Docker
- Linux
- AI engineering practice
- LangGraph
- MCP
- LLM evaluation
- natural-language cases
- locator recovery
- execution evidence
- repair review
- Quality and delivery
- Test strategy
- release gating
- CI/CD
- defect retrospectives
- architecture review
- continuous health checks
- Trace
- Prometheus
Education
Education
- 2020 — 2023
Beihang University (北京航空航天大学)
Computer Science and Technology · Bachelor's (continuing education)
- 2010 — 2012
Anyang Normal University (安阳师范学院)
Computer Network Technology · Associate degree