Staff Quality Engineer - AI SOC

At Arctic Wolf, you will not just watch the cybersecurity industry evolve – you will help lead the change. Our global team is made up of people who thrive on solving complex problems, moving quickly, and building technology that protects organizations around the world. We are proud to be recognized by Forbes, CNBC, Fortune, CRN, Gartner Peer Insights, and International Data Corporation MarketScape. What matters most is the work behind these recognitions: delivering real outcomes for customers through award-winning innovation such as our Aurora Platform.If you are looking for meaningful work, smart teammates, and the opportunity to make a real impact in a high-growth company that is redefining security operations, Arctic Wolf is the right place for you.Our mission is simple: End Cyber Risk.We are looking for a Staff Quality Engineer - Artificial Intelligence to help achieve this mission.The Staff Quality Engineer will contribute to our Engineering organization by building scalable automation frameworks and quality engineering solutions for artificial intelligence, machine learning, and cybersecurity applications. This role will focus on ensuring reliability, scalability, performance, and quality across distributed systems, cloud-native services, and large language model-driven applications. The Arctic Wolf security operations platform ingests and processes more than 600 billion events per day from a wide variety of on-premises devices and cloud platforms. The security pipeline is a distributed system of loosely coupled microservices that power real-time analysis and threat detection systems. These services transform incoming events into actionable intelligence used by Arctic Wolf Security Services teams to help protect customers.IN THIS ROLE, YOU WILL:• Create and extend software frameworks and tools to execute, monitor, and report on automated tests• Build and maintain automation frameworks and continuous integration and continuous delivery pipelines• Review testing strategies, approaches, and test plans while providing guidance to development teams• Architect, design, and build automation solutions for application programming interface validation, performance testing, load testing, and fuzz testing• Develop and maintain testing frameworks for generative artificial intelligence and machine learning applications• Validate model behavior, prompt-response consistency, hallucination detection, and regression testing for artificial intelligence inference application programming interfaces• Implement evaluation pipelines to measure large language model accuracy, latency, bias, toxicity, and reliability• Collaborate with highly skilled software engineering professionals across teams• Continuously improve engineering quality, automation practices, and testing methodologies• Learn and adopt emerging technologies in artificial intelligence, cybersecurity, cloud engineering, and distributed systemsOUR TECHNOLOGY STACK INCLUDES:• Selenium• Playwright• Doc...