• Design and build simulation environments that model CTV auction mechanics, inventory supply, and advertiser competition • Develop counterfactual and what-if frameworks for evaluating bidding strategies, budget allocation, and pacing algorithms offline • Build AI agents that explore strategy spaces, generate hypotheses, and automate experimentation within simulated environments • Use LLMs and generative AI to accelerate internal ML workflows — synthetic data generation, code generation, automated analysis, and rapid prototyping • Use simulation to de-risk ML model deployments — validate new bidding and optimization strategies before they touch live traffic • Define the technical direction for simulation and AI infrastructure and mentor engineers on the team