AI GTM Transformation Lead

NetApp, Inc.•Durham, NC

4d•$196,350 - $292,600

About The Position

AI is changing how go-to-market teams operate. We are seeking an AI GTM Transformation Lead to lead the end-to-end AI transformation of our Go-to-Market (GTM) Revenue Operations organization. This is a highly strategic, senior individual contributor role responsible for shaping how AI is applied across GTM RevOps, turning fragmented ideas into a coherent portfolio of scalable, governed, high-value transformation initiatives. This leader will sit across the business and act as the connective tissue between the business, AI technologies, and execution teams. The role focuses on redesigning business outcomes using AI-native thinking, leveraging AI agents, orchestration layers, automation platforms, and human-in-the-loop systems to fundamentally transform how work gets done. The role goes beyond automation delivery. It requires someone who can define the outcome design for AI transformation, redesign workflows for human-agent collaboration, guide initiatives from proof of concept through scaled autonomy, and ensure success is measured not only by deployment, but by adoption, trust, and business value.

Requirements

Typically requires a minimum of 15 years of related experience
Deep experience in Revenue Operations, GTM Operations, Sales Operations, Customer Operations, Solutions Engineering, or a closely related GTM function, with a strong understanding of how go-to-market teams operate end to end.
Proven ability to lead complex, cross-functional transformation initiatives that require influence across business, technical, and operational stakeholders.
Strong program and portfolio orchestration skills, including prioritization, dependency management, executive communication, and delivery alignment across multiple initiatives.
Experience designing workflows, service models, or operating processes that span people, systems, data, and governance.
Strong understanding of AI-assisted workflows, copilots, agentic automation, or intelligent process redesign.
Ability to define value cases, KPIs, and success metrics for transformation programs and hold initiatives accountable to business outcomes.
Experience working with ambiguity and building new operating models or capabilities where no playbook exists.
Excellent executive presence and communication skills, with the ability to synthesize complex issues and influence senior leaders.
Comfort partnering with technical teams and working across APIs, prompts, automation platforms, AI tools, and data/system dependencies, even if not acting as the primary engineer.
Demonstrated ability to simplify complex concepts and enable broad adoption among non-technical users.

Responsibilities

Lead AI-Driven GTM Transformation: Own the GTM RevOps AI transformation roadmap, aligning AI initiatives to business priorities, operational outcomes, and measurable value. Serve as the strategic leader connecting business goals, process design, governance, adoption, and execution.
Build and Prioritize the AI Portfolio: Identify, assess, and prioritize high-impact AI, automation, and workflow transformation opportunities. Partner with stakeholders to define business requirements, future-state processes, success metrics, dependencies, and governance needs. Prepare initiatives for investment and portfolio review through structured evaluation and prioritization.
Design Human + AI Operating Models: Reimagine workflows to optimize collaboration between people and AI agents. Define autonomy levels, exception handling, governance controls, and scalability requirements. Drive initiatives from proof-of-concept through pilot and enterprise-scale deployment.
Drive Cross-Functional Delivery: Coordinate business, data, platform, and AI delivery teams to execute transformation initiatives. Translate business needs into requirements, user stories, acceptance criteria, and operational processes. Ensure solutions are scalable, integrated, and aligned with enterprise governance standards.
Shape Governance and Adoption: Contribute to AI governance forums, prioritization decisions, and operating model design. Ensure appropriate attention to risk, security, compliance, and data governance. Partner with change leaders to build adoption, enablement, and trust across GTM teams.
Measure Impact and Continuous Improvement: Establish and track metrics for adoption, productivity, quality, efficiency, and business impact. Use operational insights and user feedback to refine solutions, improve agent performance, and evolve the AI roadmap. Stay current on emerging AI capabilities and identify opportunities that create practical business value.