Responsibilities include defining the long-term vision, strategy, and roadmap for Docusign's AI Platform, establishing core capabilities that enable AI innovation across the Intelligent Agreement Management ecosystem. You will lead platform initiatives across product domains such as IAM, CLM, and collaboration with B2I teams to deliver shared platform investments that accelerate AI adoption while reducing duplicated engineering effort. You will drive the global AI strategy to enable globalization and deliver enterprise-ready AI experiences across international markets.

Key work streams: - Build the foundational admin interface for AI assistants and autonomous agents, including observability, knowledge integration, extensibility, and scalable governance suitable for enterprise use. - Define the enterprise usage framework for AI, covering administrative controls, policy management, usage governance, MCP integration, compliance, and configurable platform controls. - Shape the strategy for multi-model AI, enabling seamless integration of frontier foundation models while optimizing quality, performance, reliability, latency, and cost. - Partner with Engineering and Applied AI to define platform architecture, investments, and long-term AI infrastructure strategy. - Establish platform metrics to measure adoption, quality, reliability,

Responsibilities include defining the long-term vision, strategy, and roadmap for Docusign's AI Platform, establishing core capabilities that enable AI innovation across the Intelligent Agreement Management ecosystem. You will lead platform initiatives across product domains such as IAM, CLM, and collaboration with B2I teams to deliver shared platform investments that accelerate AI adoption while reducing duplicated engineering effort. You will drive the global AI strategy to enable globalization and deliver enterprise-ready AI experiences across international markets.

Key work streams: - Build the foundational admin interface for AI assistants and autonomous agents, including observability, knowledge integration, extensibility, and scalable governance suitable for enterprise use. - Define the enterprise usage framework for AI, covering administrative controls, policy management, usage governance, MCP integration, compliance, and configurable platform controls. - Shape the strategy for multi-model AI, enabling seamless integration of frontier foundation models while optimizing quality, performance, reliability, latency, and cost. - Partner with Engineering and Applied AI to define platform architecture, investments, and long-term AI infrastructure strategy. - Establish platform metrics to measure adoption, quality, reliability,