Lead AI Test Automation Architect - Hybrid

Wolters Kluwer N.V.

Coppell (TX)

Hybrid

USD 89,600 - 157,000

Full time

14 days+

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Benefits offered by this job

Medical, Dental & Vision Plans
401(k)
Paid Parental Leave
Tuition Assistance Plan

Job summary

Wolters Kluwer N.V. Coppell, TX, is seeking a Lead Test Automation Architect to define an enterprise-grade automation strategy across UI, API, data and platform layers, with a focus on Agentic AI / LLM-based systems.

You will architect scalable frameworks and drive engineering excellence to accelerate delivery through productive automation programs. You will lead architectural decisions, mentor engineers, and partner with Product and ML/AI teams to establish acceptance criteria, quality gates,

Qualifications

  • 8–12+ years in Quality Engineering / Test Automation with architect-level ownership.
  • Experience designing scalable automation across API, UI and data layers.
  • Strong programming skills in at least one modern language (Java, Python, TS/JS, C#).
  • Expertise in UI/API/contract testing and CI/CD integration.

Responsibilities

  • Define and own the test automation architecture and multi-layer strategy.
  • Establish automation standards, patterns, and reference implementations.
  • Drive shift-left testing and reduce reliance on fragile end-to-end tests.
  • Lead QA for AI/LLM features, alignment tests, and evaluation harnesses.
  • Mentor engineers, review automation PRs, and shape roadmaps.

Skills

Java
Python
TypeScript/JavaScript
C#
Architecture ownership

Tools

Playwright
Cypress
Selenium
REST-assured
Postman
Newman
pytest
GitHub Actions
Jenkins
Azure DevOps

Job description

Wolters Kluwer N.V. Coppell, TX, is seeking a Lead Test Automation Architect to define an enterprise-grade automation strategy across UI, API, data and platform layers, with a focus on Agentic AI / LLM-based systems.

You will architect scalable frameworks and drive engineering excellence to accelerate delivery through productive automation programs. You will lead architectural decisions, mentor engineers, and partner with Product and ML/AI teams to establish acceptance criteria, quality gates,

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