Staff Quality Engineer - AI SOC

Requirements

• Experience testing artificial intelligence or machine learning applications
• Familiarity with large language model evaluation techniques and prompt engineering
• Experience working within cybersecurity or cloud-native environments
• Experience building scalable testing infrastructure for distributed systems
• WHAT SUCCESS LOOKS LIKE:
• Scalable and reliable automated testing frameworks supporting high-throughput distributed systems
• Improved software quality, reliability, and deployment confidence across engineering teams
• Comprehensive validation pipelines for artificial intelligence and machine learning systems
• Proactive identification of quality, performance, and scalability issues before production

Additional Information

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 Senior Quality Engineer - Artificial Intelligence Integration to help achieve this mission. The Senior 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 systems OUR TECHNOLOGY STACK INCLUDES: - Selenium - Playwright - Docker - Kubernetes - Amazon Web Services including Bedrock, Lambda, Simple Queue Service, and Simple Storage Service - LangChain - Large language model evaluation frameworks such as Ragas - OpenAPI - PostgreSQL - Linux YOU WILL BE SUCCESSFUL IN THIS ROLE IF: - You are excited to work at the intersection of artificial intelligence, machine learning, big data, and cybersecurity - You have more than 8 years of experience delivering high-quality software solutions - You are passionate about driving software quality through automation and testing - You have experience deploying services on cloud computing platforms such as Amazon Web Services, Microsoft Azure, or Google Cloud Platform - You have strong expertise with tools used for functional testing, load testing, and fuzz testing such as Locust and CATS - You have experience building automation frameworks and continuous integration and continuous delivery pipelines - You have experience working with distributed systems and microservices architectures - You possess strong programming, debugging, and problem-solving skills in modern software engineering environments - You continuously adapt to emerging technologies, testing methodologies, and engineering best practices

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