Quality Assurance Architect

Required Skills & Experience

Hands‑On Technical Skills

• Write, review, and analyze code in languages commonly used in QA automation, including:

○ Java

○ C#

○ Python .

• Formerly a software engineer and moved into QA

• Understand advanced AI concepts such as:

○ LLM architecture

○ Model prompting and fine-tuning

○ Hallucination detection and mitigation strategies

Job Description

This role focuses on helping companies understand how they're currently using AI and where they can get more value out of it. You'd lead conversations with customers to learn how their AI setup works today, why they chose certain tools or models, and whether they're using things like large language models and how those are built and maintained. From there, you'd help turn their goals, like saving time, cutting costs, or improving efficiency, into a clear plan they can actually execute.

A big part of the role is also finding practical ways to use AI within QA teams. You'd guide companies on how to modernize their testing approach by recommending the right tools based on where they are today. For example, helping teams move from older tools like Selenium to newer ones like Playwright, supporting teams transitioning from manual to automated testing with tools like Tosca, or suggesting low-code automation platforms for teams that don't have deep engineering resources. Overall, the role is about making AI and QA more practical, efficient, and easy to scale in real-world environments.