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Docusign

Runs electronic signing and agreement workflows

AI Transformation Director

Program ManagementUpdated on Nov 13
Full-timeSan Francisco, CA, USA

About the Job

Requirements

  • Experience in SaaS sales operations, including designing sales compensation structures, managing quota allocation, and optimizing territory models in large-scale enterprise environments.
  • At least 15 years of leadership and program delivery experience within Go-To-Market operations, Revenue Operations, and GTM strategy in enterprise SaaS environments.
  • At least 6 years of specialized leadership in applied AI, machine learning automation, and operationalizing LLM agent applications.
  • Experience designing and scaling multi-workstream AI transformation roadmaps across complex, global Go-To-Market motions, including Sales, Customer Success, Marketing, Digital, CPQ, and Billing.
  • Experience with AI system architecture, including multi-agent frameworks such as LangGraph, AutoGen, and CrewAI; LLM orchestration; RAG systems; vector databases; and modern Go-To-Market data platforms such as Snowflake, Reverse ETL, and CDPs.
  • Experience with core SaaS financial metrics, including ARR, NRR, LTV, CAC payback, and pipeline velocity.
  • Experience presenting to, influencing, and aligning C-suite leadership on disruptive strategy, build-versus-buy decisions, and technology investments.
  • Bachelor's degree in Computer Science, Data Science, Engineering, or a related technical or quantitative field.

Responsibilities

  • Apply deep expertise in SaaS sales models, compensation design, quota setting, and territory optimization by integrating these domain-specific business rules into autonomous AI agent logic to align with financial and operational objectives.
  • Launch pilots and scale successful pilots globally, drive representative enablement, track friction, and manage culture change.
  • Own the end-to-end lifecycle of complex AI agent program rollouts, from conceptualization and development through pilot design, rollout governance, representative enablement, friction tracking, and global scaling; establish readiness gates and iteration frameworks.
  • Define target populations, pilot and control cohorts, sequencing, and rollout approaches.
  • Track adoption by cohort, identify underperformance, provide root-cause analysis, and develop action plans.
  • Mobilize front-line managers, Enablement, Product, or Operations when adoption requires correction.
  • Determine when to iterate, scale, pause, or transition initiatives into run-the-business ownership.
  • Connect AI transformation to enterprise financial levers by maximizing LTV, shortening CAC payback periods, accelerating pipeline and funnel velocity, and lowering cost-to-serve.
  • Integrate SaaS sales models, compensation design, quota setting, and territory optimization rules into autonomous AI agent logic to support financial and operational alignment.
  • Serve as a trusted advisor to the CRO, CMO, CTO, and VP of Transformation; align AI capabilities with growth metrics, drive change management across global revenue teams, and establish the senior-leader cadence needed for accountability and adoption.
  • Establish enterprise-grade standards for Responsible AI, model drift monitoring, hallucination prevention, data security, and auditability across automated revenue motions.
  • Define global patterns, reusable agent architectures, Agentic UI standards, and governance protocols to enable secure scaling across global Go-To-Market regions.
  • Direct cross-functional pods across Engineering, Applied AI, Revenue Operations, Product, and Data Platform to deploy production-grade agentic platforms, custom RAG integrations, and autonomous action engines.
  • Continuously evaluate market trends in LLM orchestration, multi-agent frameworks, and sales intelligence to keep the Go-To-Market technology stack current.
  • Lead change management across global revenue teams to drive organizational readiness, culture shifts, and sustained adoption of autonomous AI systems.
  • Lead AI agent programs from conceptualization and development through deployment and performance monitoring; establish program management frameworks for agent interdependencies, lifecycle governance, and integration so autonomous systems deliver reliable, high-value outcomes aligned with enterprise goals.
  • Design and launch pilots, scale pilots that pass readiness gates globally, drive representative enablement, track friction, and manage culture change.

Desired Qualifications

  • Master's degree in Data Science, Computer Science, or Management Information Systems, or an MBA.
  • Recognized industry thought leadership in AI for Revenue Operations, AI Go-To-Market Systems, or Agentic AI Workflows.
  • Expertise leading build-versus-buy evaluations for enterprise AI tools and negotiating key technology partnerships.
  • Track record of successfully executing multi-million-dollar AI or digital transformation portfolios that deliver measurable financial return on investment.

About the Company

Docusign

Runs electronic signing and agreement workflows

Docusign runs electronic signing and agreement management software for businesses, letting people approve contracts online and track the steps around each agreement. Its eSignature product routes documents to signers and records who signed, while contract lifecycle tools organize preparation, negotiation, and approvals. The Intelligent Agreement Management platform stores contracts in a searchable repository and uses AI to extract terms and connect agreement data to business workflows. Customers use its web applications or embed signing through APIs, and pay for subscriptions based on users, features, and document allowances. Docusign was founded in 2003 and is headquartered in San Francisco.

Company size
5,001-10,000
Company stage
IPO
Headquarters
San Francisco, CA
Founded
2003

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