We are seeking a Sr. CS Transformation & AI Manger to help accelerate the next generation of Customer Success. 

This role sits at the intersection of CS transformation, technology, data, and AI, with a mandate to turn our transformation strategy into new ways of working. This person will identify where AI, automation, customer intelligence, and emerging technologies can simplify work, improve decision-making, increase team capacity, and enable more proactive and impactful customer engagement. 

This is not a traditional CS strategy role or a pure AI engineering role. We are looking for a transformation leader with deep applied-AI fluency and a builder's mindset—someone who can connect business problems to technical possibilities, rapidly prototype solutions, and partner across CS, Product, Engineering, Data, and Operations to bring the best ideas to scale. 

The opportunity is bigger than deploying AI tools. It's about fundamentally rethinking how Customer Success operates in an AI-enabled world. 

You are a strategic problem solver, technologist, builder, and transformation leader, who sees AI not simply as another tool, but as an opportunity to fundamentally rethink how Customer Success operates. 

You bring: 

• Deep understanding of Customer Success, SaaS, and GTM operating models. 

• Strong applied-AI fluency and a point of view on how AI will reshape Customer Success. 

• A builder's mentality with an operator's discipline—comfortable experimenting and prototyping, while accountable for getting solutions adopted and scaled. 

• Strong systems thinking across people, process, data, technology, and customer experience. 

• The ability to move comfortably between business strategy and technical execution. 

• A bias toward action and a track record of turning ambiguous problems into tangible solutions. 

• Strong cross-functional influence and the ability to create momentum across complex organizations. 

• Curiosity and a desire to continuously experiment, learn, and push what's possible.

Qualifications & Experience 

Required 

• 6+ years of experience across Customer Success, SaaS, GTM transformation, technology strategy, product, AI/automation, or related disciplines. 

• Demonstrated experience leading cross-functional transformation or technology initiatives within CS, post-sales, or broader GTM organizations. 

• Proven experience applying AI, automation, and data to solve real business problems. 

• Strong working knowledge of modern AI capabilities, including LLMs, AI agents, APIs, integrations, workflow automation, and enterprise data. 

• Hands-on experience prototyping AI-enabled workflows, agents, automations, or similar solutions. 

• Experience with enterprise GTM technology ecosystems such as Salesforce, Gainsight or comparable CS platforms, data/BI platforms, and workflow automation technologies. 

• Demonstrated ability to partner effectively with Engineering, Data, Product, IT, Security, and Operations. 

• Proven ability to move complex initiatives from strategy through execution, adoption, and measurable business impact. 

What Success Looks Like 

Success means we aren't simply using more AI, we are operating Customer Success differently because of it. 

CS teams spend less time searching for information and performing manual work, customer intelligence becomes more proactive and actionable, and teams have greater capacity to focus on strategic customer engagement and value. 

Most importantly, AI and transformation become a measurable business capability—not a collection of tools, pilots, and experiments

Transform the CS Operating Model 

• Partner with CS leadership to translate the future-state vision for Customer Success into clear initiatives, workstreams, and execution plans. 

• Evaluate how work gets done today and identify where workflows should be eliminated, automated, augmented, or fundamentally redesigned. 

• Lead high-priority transformation initiatives that improve CS productivity, scalability, proactive engagement, and customer impact. 

• Bring a builder's mentality with an operator's discipline - moving beyond ideas and pilots to capabilities that are adopted, scaled, and delivering measurable value. 

• Coordinate across teams, manage dependencies, surface risks, and keep transformation initiatives moving with speed. 

Advance the CS Intelligence Layer 

• Help evolve the intelligence layer that connects customer signals across systems and uses AI to identify what matters, why it matters, and what action should happen next. 

• Partner across CS, Data, Product, and Operations to bring together signals such as product adoption, engagement, sentiment, support, relationship, lifecycle, and commercial data. 

• Translate customer intelligence into prioritized insights, risk and opportunity signals, and next-best actions for CS teams. 

• Help embed intelligence directly into CS workflows rather than creating more dashboards, tools, or places for teams to look. 

• Create closed-loop mechanisms that turn customer and CSM signals into intelligence, action, and measurable outcomes. 

Architect & Rapidly Prototype AI-Enabled Solutions 

• Translate CS business problems into AI-enabled workflows, solution concepts, data requirements, and technical approaches. 

• Rapidly prototype agents, automations, and AI-enabled workflows to test ideas and demonstrate what's possible, and accelerate decision-making. 

• Bring enough technical depth to work credibly across LLMs, agents, APIs, integrations, automation, enterprise data, and modern AI platforms. 

• Evaluate potential solutions and provide recommendations on when to build, buy, integrate, or leverage existing enterprise capabilities. 

• Partner closely with Engineering, Data, IT, Security, and Architecture teams to transition validated concepts into secure, scalable, production-ready capabilities. 

This role is not expected to be the production engineer for every solution. It does require someone technical enough to explore, prototype, make informed solution decisions, and effectively bridge the gap between Customer Success strategy and technical execution. 

Drive Adoption & Business Impact 

• Move initiatives from idea 12 prototype 12 pilot 12 production 12 adoption 12 measurable impact. 

• Partner with CS leaders and Enablement to ensure new capabilities translate into meaningful workflow and behavior change. 

• Establish success criteria and feedback loops to continuously improve solutions based on field usage and customer impact. 

• Measure transformation through improvements in productivity, capacity, adoption, proactive risk identification, retention, growth, and customer outcomes. 

• Provide clear visibility into progress, impact, dependencies, and decisions required to keep transformation moving with speed. 

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