Lead Software Test Automation Engineer

Wolters Kluwer DXG U.S., Inc.; Coppell (TX); On-site; USD 90,000 - 157,000; Full time

Job summary

Wolters Kluwer International seeks a Lead Software Test Automation Engineer to define and lead an enterprise-grade test automation strategy across UI, API, data, integration, and platform layers, advancing quality engineering for AI-enabled systems.

You will design scalable automation frameworks, set measurable quality gates, and embed automation into CI/CD with production-grade practices, collaborating with AI, security, DevOps, and Product teams.

Qualifications

• 8+ years of software quality engineering or test automation experience.
• Experience building scalable automation across API, UI, data, and end-to-end layers.
• Strong programming skills in Java, Python, TypeScript/JavaScript, or C#.
• Hands-on with Playwright, Cypress, Selenium, REST Assured, Postman, or pytest.
• Experience integrating automated testing into CI/CD (GitHub Actions, Jenkins, Azure DevOps).
• Experience validating AI/ML in production-oriented software with evaluation harnesses and benchmarks.
• Knowledge of test data management, environments, and dependency control.

Responsibilities

• Define and own the test automation design and multi-layer strategy.
• Establish automation standards, patterns, and reusable components.
• Drive shift-left quality practices and pre-merge validation.
• Design validation for non-deterministic AI outcomes and groundedness.
• Build high-throughput automation suites across products.
• Embed automated validation into CI/CD with gates and release-readiness criteria.

Skills

Programming languages

Automation frameworks

CI/CD integration

AI/ML validation

Quality engineering

Education

Bachelor’s degree in CS/SE/IS

Master’s degree preferred

Tools

Playwright

Cypress

Selenium

REST Assured

Postman/Newman

pytest

GitHub Actions

Jenkins

Azure DevOps

Job description

We are seeking a Lead Software Test Automation Engineer to define and lead an enterprise-grade test automation strategy across UI, API, data, integration, and platform layers while evolving our quality engineering capabilities for AI and agentic systems. This role will design and scale automation frameworks, establish measurable quality gates for deterministic and non-deterministic product behavior, and drive reliable, maintainable automation that accelerates delivery. The engineer will define validation approaches for probabilistic AI outcomes, including evaluation datasets, threshold- and rubric-based validation, groundedness, regression detection, robustness, performance, and reliability, while embedding automation into CI/CD and production-quality practices.

Essential Duties and responsibilities

Define and own the test automation technical design and risk-based, multi-layer strategy across UI, API, contract, component, integration, end-to-end, data, and platform testing. Establish automation standards, patterns, and reference implementations covering framework structure, coding practices, reusable components, test data, diagnostics, reporting, and maintainability. Drive shift-left quality practices through component, contract, API, and pre-merge validation, reducing unnecessary reliance on slow or fragile end-to-end tests. Design and implement validation approaches for non-deterministic AI and agentic outcomes, including confidence- and threshold-based assertions, semantic and rubric-based evaluation, benchmark datasets, evaluation harnesses, groundedness testing, and regression detection across model, prompt, context, and agent changes. Define AI quality coverage and measurable acceptance criteria across accuracy, robustness, groundedness, safety where applicable, performance, reliability, and cost-aware execution in partnership with AI Engineering, Product, and Software Engineering. Build and scale high-throughput automation suites that are reliable, fast, diagnosable, and easy to extend across products and delivery teams. Improve automation execution time and stability through parallelization, intelligent test selection, dependency control, deterministic test data, and disciplined retry strategies. Integrate automated validation into CI/CD with appropriate pull‑request checks, scheduled suites, deployment gates, and release‑readiness criteria. Standardize test observability, including logs, traces, screenshots or video where appropriate, artifacts, failure diagnostics, and actionable quality dashboards covering execution health, flakiness, coverage, and escaped defects. Define effective practices for test environments, test data management, service virtualization, external dependency control, and repeatable environment setup. Serve as the technical authority for software test automation; lead design and code reviews, coach engineers on automation design and code quality, and establish maintainable engineering standards. Influence product and engineering roadmaps by translating customer, technical, operational, and delivery risks into clear validation priorities and quality investments. Partner with Product, Software Engineering, AI Engineering, Security, DevOps, and Operations to ensure functional and nonfunctional quality is engineered throughout the product lifecycle. Use production telemetry, incidents, customer issues, and defect escape patterns to continuously improve automated coverage and prevent recurrence.

Job Qualifications

Education

Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related field, or equivalent practical experience. Master’s degree in a relevant technical or business discipline is preferred.

Required Experience / Skills

• 8+ years of software quality engineering or test automation experience, including significant ownership of automation frameworks, technical design, and strategy for complex commercial software.
• Hands‑on experience designing and building scalable automation across API, contract, integration, UI, data, and end‑to‑end layers.
• Strong programming skills in at least one modern language such as Java, Python, TypeScript/JavaScript, or C#.
• Hands‑on experience with modern UI and API automation frameworks such as Playwright, Cypress, Selenium, REST Assured, SuperTest, Postman/Newman, or pytest.
• Experience integrating automated testing into CI/CD using platforms such as GitHub Actions, Jenkins, or Azure DevOps, including automated quality gates and release‑readiness criteria.
• Demonstrated ability to improve test reliability and execution speed through engineering solutions, including reducing flakiness, parallelization, test selection, and effective diagnostics.
• Experience defining test data strategies, managing test environments, service virtualization, and dependency control for distributed systems.
• Hands‑on experience validating AI/ML, generative AI, agentic, or other probabilistic product capabilities in production‑oriented software, including evaluation harnesses, benchmark datasets, semantic or rubric‑based scoring, groundedness, and regression evaluation.
• Practical experience with Agentic Product Development Lifecycle and Spec‑Driven Development, including translating specifications and acceptance criteria into traceable automated validation.
• Working knowledge of security, performance, accessibility, resilience, and reliability testing within modern software delivery practices.

Knowledge, Skills, and Abilities

Strong test automation design and systems‑thinking skills, with the ability to design automation across application, API, integration, data, platform, and AI/agentic boundaries. Deep understanding of modern quality engineering practices, including the test pyramid, shift‑left validation, contract testing, risk‑based testing, and appropriate use of end‑to‑end automation. Strong understanding of testing probabilistic AI and agentic systems, including evaluation design, benchmark datasets, thresholds, semantic and rubric‑based scoring, groundedness, robustness, regression, and traceability. Ability to design automation for speed, determinism, maintainability, diagnosability, and reuse while avoiding brittle or over‑engineered frameworks. Strong understanding of CI/CD, automated quality gates, test observability, telemetry, environment strategy, and production feedback loops. Ability to define meaningful quality measures and dashboards that distinguish product risk and release confidence from simple test counts or pass rates. Strong coding, code‑review, debugging, and root‑cause analysis skills with an engineering‑first approach to test automation. Ability to lead through technical influence, establish automation standards, coach engineers, and drive quality ownership across Product, Software Engineering, AI Engineering, DevOps, and Operations. Strong communication skills with the ability to translate technical and product risk into clear testing priorities, quality decisions, and pragmatic trade‑offs. Ability to balance delivery speed, automation coverage, reliability, maintainability, and business risk without positioning Quality Engineering as a downstream gate.

Compensation

Compensation: $89,600.00 - $157,000.00 USD This role is eligible for Bonus. Compensation range listed is based on primary location of the position. Actual base salary offer is influenced by a wide array of factors including but not limited to skills, experience and actual hiring location.

Additional Information

Wolters Kluwer offers a wide variety of competitive benefits and programs to help meet your needs and balance your work and personal life, including but not limited to:

• Medical, Dental, & Vision Plans, 401(k), FSA/HSA, Commuter Benefits, Tuition Assistance Plan, Vacation and Sick Time, and Paid Parental Leave.

Full details of our benefits are available upon request.

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Join us, at Wolters Kluwer, and be part of a dynamic global technology company that makes a difference every day. We’re innovators with impact. We provide expert software and information solutions that the world’s leading professionals rely on, in the moments that matter most. You’ll make a real difference in the lives of millions of people.

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Wolters Kluwer reported 2025 annual revenues of €6.1 billion. The group serves customers in over 180 countries, maintains operations in over 40 countries, and employs more than 21,000 people worldwide. Our customers work in industries that impact the lives of millions of people every single day. Our mission is to empower our professional customers with the AI‑powered solutions they need to make critical decisions, achieve successful outcomes, and increase productivity. We deliver trusted, AI‑powered expert solutions that combine deep domain knowledge, proprietary content, and advanced technology to provide expert‑validated insights, automate workflows, and drive better outcomes. Today, nearly 70% of our digital revenues come from AI‑powered solutions, reflecting our strategic focus on embedding AI into professional workflows and delivering measurable productivity gains. We are committed to helping professionals navigate complexity, improve the way they work, and solve critical challenges through cloud‑based, AI‑powered platforms that integrate seamlessly into their workflows and ecosystems. Our solutions are designed to deliver impact when it matters most, especially in high‑stakes environments where accuracy and trust are essential. With a nearly 190‑year legacy, Wolters Kluwer continues to evolve its portfolio of digital solutions and services to meet the changing needs of professionals worldwide, enabling them to work faster, make smarter decisions, and deliver better outcomes.

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