• Drive the identification and prioritization of 3-5 high-potential experiments based on the newest research developments, serving as the key driver of experimental flow and ensuring cutting-edge techniques (e.g., novel prompting strategies, reasoning approaches, or model optimizations) are evaluated and integrated to measurably improve product performance. • Build and maintain a comprehensive experimentation infrastructure that enables the team to run AI-facilitated experiments at scale, combining AI evals with A/B testing capabilities to empower rapid experimentation and evaluation across the product. • Drive high-impact product releases powered by AI innovations, translating cutting-edge research into shipped features that demonstrably improve user experience and key product metrics. • Accelerate engineering adoption of AI capabilities across the organization by working closely with the CTO to integrate AI tooling into internal workflows, enabling engineers to leverage AI effectively in their day-to-day work and ship research-driven features. • Establish a culture of AI expertise and knowledge sharing by identifying and disseminating high-potential research, helping build team capabilities in AI evals, context engineering, and related areas through consistent contribution and fast-follow implementation.