• Set the engineering vision and direct the architecture of ServiceTitan's core AI infrastructure and Multi-Agent Systems encompassing model hosting/training, agent hosting, reinforcement learning, intelligence store and rigorous evaluation that bridges agent specifications to business outcomes. • Partner with Product leaders to co-create vision, set strategic direction, and define the technical roadmap for foundational AI capabilities, ensuring the infrastructure seamlessly scales to support all platform-level agents and future product innovations. • Define enterprise-wide standards, budgets, and governance for LLM capabilities and trade-offs (latency, cost) to drive superior customer experiences at scale. • Oversee highly available data processing architectures, Enterprise-wide Knowledge Graphs, and the foundational Intelligence Store, and feedback loops essential for successful RAG and agentic pipelines. • Architect and drive the adoption of scalable LLMOps and AgentOps frameworks. • Direct the architectural integration of advanced techniques (multi-agent systems, function calling, fine-tuning) to enhance agent capabilities and drive operational excellence across the organization. • Align with Engineering and Product leadership on roadmaps to ensure timely delivery of robust production agents that drive revenue and growth. • Implement governance for ethical, explainable, and compliant AI usage, including data handling and bias considerations. • Hire, mentor, and retain a high-performing AI Engineering organization, including developing and coaching engineering managers.