Principal AI Quality Engineer
Confirmed on the employer's own hiring board on Oct 17, 2026. First seen by Alion on Jul 13, 2026.
Join Fourth, a global technology company, as a Principal AI Quality Engineer. In this role, you will define and drive the AI-driven global QA strategy, shape how quality is engineered across Fourth's systems, and establish the QA tools, frameworks, standards, and ways of working. You will also act as the principal point of escalation for complex testing and quality challenges, champion modern testing technologies, and lead Fourth's QA approach for AI development. This is an exciting opportunity to leave a lasting mark on how software quality and AI come together at scale.
Missions
- Definir, poseer y evolucionar continuamente la estrategia y la hoja de ruta de QA global impulsada por la IA de Fourth, alineada con las hojas de ruta de Producto y Tecnología.
- Establecer las herramientas, marcos, estándares y formas de trabajo de QA en toda la organización de ingeniería global para lograr los objetivos tecnológicos.
- Actuar como el principal punto de escalación para desafíos complejos de pruebas y calidad en equipos de ingeniería globales, movilizando la experiencia en la materia para resolverlos.
Profil recherché
- Strong experience with Agile software delivery at scale- Track record of defining and analysing quality KPIs and quality gates
- Experience establishing test automation best practice, both functional and non-functional, across multiple teams
- Proven experience defining and implementing QA strategy at an organisational or enterprise scale
- Demonstrable experience shaping or leading a QA approach for AI-assisted and/or agentic AI development
- Experience creating and owning technical strategy and process documentation
- Excellent communication and stakeholder-management skills, with fluent English (written and spoken)
- Strong understanding of the testing and quality challenges of non-deterministic, ML/LLM-based, and agentic systems, including evaluation, guardrails, and the regression of model-driven behaviour
- Ability to influence and provide technical leadership and mentoring across senior engineering and product stakeholders
- Exposure to prompt design and prompt/response evaluation techniques for AI-enabled features
- Familiarity with MLOps or LLMOps practices, and with monitoring and observing the behaviour of AI systems in production
- Strong programming proficiency in C# or Java
- Proven ability to design and implement robust, scalable QA test strategies and automation frameworks
- Expertise in web and API testing, including hands-on UI automation with modern tools such as Playwright (or comparable frameworks)
- A practical understanding of how AI is reshaping software delivery and the new quality risks it introduces, with the drive to keep Fourth’s testing practices at the leading edge
- Practical experience using AI-assisted development tools (such as GitHub Copilot or similar), with a clear understanding of how to assure the quality, security, and maintainability of AI-generated code
- Hands-on experience with performance, security and non-functional testing
- Experience with observability tooling such as Prometheus, Grafana, and Sumo Logic
- Experience with CI/CD tooling, e.g. Jenkins, Azure DevOps, and Octopus Deploy