The role involves designing and architecting scalable AI solutions for a continuous testing platform. The individual will lead the development of systems that derive insights from test data and production environments to improve software quality. Responsibilities include creating architectures for automated failure analysis, test case generation, and the integration of production error reporting. The position requires collaborating with data engineering teams to optimize data pipelines and ensuring the effective use of cloud-based AI platforms. Additionally, the role provides technical leadership and mentorship to engineering teams while evaluating new technologies to enhance product offerings.

Candidates must possess a Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. A minimum of seven years of experience in software development and the architecture of production-grade systems is required. Applicants need extensive experience in designing and deploying large-scale AI/ML systems, specifically within cloud environments like GCP. Proficiency in Generative AI, including LLMs and prompt engineering, is essential, alongside a strong background in big data and analytics.