Customer Success Automation Specialist

Are you ready to define the future of Customer Success? We are looking for our new CS Automation Specialist where you will be the strategic architect and owner of our entire AI agent program across Customer Success and post-sales. This is a unique opportunity to build and scale cutting-edge autonomous agents, translating deep CS domain knowledge and systems thinking into impactful business outcomes. If you are passionate about pushing the frontier of agentic AI and driving transformative operational efficiency, this challenge is for you.

In this role, you will…

• Own the full AI agent programme for Customers Success
• Design the business logic each CS agent follows: what triggers it, what data it reads, what action it takes
• Continuously evaluate the agent landscape, identifying gaps, redundancies and opportunities across customer success
• Research and recommend new AI tools and frameworks relevant to customer success automation
• Define and maintain the quality standards and test cases that determine whether a CS agent is ready for production
• Act as the primary strategic partner to Customers for Life leadership, translating operational needs into agent architecture decisions

Your day-to-day work and responsibilities include…

• Designing and owning the business logic for each CS agent across the full customer lifecycle
• Leading the agent roadmap for CS workstreams and making the case to leadership for where new agents create the most value
• Running structured evaluations of new customer success automation tools and recommending what to adopt or deprioritise
• Owning the recurring review cycle to ensure agents stay accurate as the customer base changes
• Tracking agent performance and communicating impact in business terms: churn risk coverage, retention
• Collaborating with automation engineers on deployment and infrastructure decisions

This position is for you if you have…

• A track record of owning and designing automation or AI systems in a CS environment: you have made architectural decisions, not just implemented them
• Deep knowledge of customer success processes and the data that drives them: health scoring, lifecycle management, renewal management and escalation handling
• Strong understanding of what lives in Gainsight and what patterns signal churn risk
• Hands-on experience evaluating and selecting AI or automation tooling in a CS context
• Practical experience with LLMs and agentic AI: you understand where agents can act autonomously and where human judgment is genuinely needed
• Strong stakeholder management: CS leaders care deeply about customer outcomes and you earn credibility by shipping things that demonstrably work
• Systems thinking: you design for coherence and long-term maintainability, not just the immediate use case