The Head of Post Sales Technology is responsible for transforming Customer Support into an AI-first, automation-led, insight-driven organization
This leader will design and execute a technology strategy where AI is not an add-on, but the foundation of how support operates — from customer self-service and intelligent routing to real-time agent augmentation and predictive service operations
The role sits in the IT organization, and will define how emerging AI capabilities fundamentally reshape customer experience, agent productivity, and cost structure
We are looking to speak to candidates who are based in Palo Alto / San Francisco or New York City for our hybrid working model
Key Responsibilities Partner with the Technical Support organization, Customer Success and Professional Services organization to understand the business objectives and chart out a technology strategy and roadmap to address their needs
1. AI-First Strategy & Transformation Define and own a multi-year AI roadmap for post sales. The capabilities should ideally include Suggested responses Knowledge article generation Case summarization Sentiment detection Next-best-action recommendations Reimagine support workflows assuming AI agents and copilots are default participants Lead transition from reactive case management to predictive, proactive service Establish governance for responsible and secure AI deployment 2. Autonomous & Conversational AI Architect scalable conversational AI platforms for chat, voice, and digital channels Lead implementation of AI solutions using modern AI native platforms Develop frameworks to measure AI containment rates, hallucination risk, escalation patterns, and customer trust Continuously tune models based on real customer interaction data 4. Intelligent Case Lifecycle & Automation Implement predictive case routing based on complexity and skill Automate repetitive workflows and approvals Use machine learning to detect systemic product issues and trigger escalation automatically Drive closed-loop feedback into Product and Engineering 5. Data, Insights & Predictive Analytics Establish unified support data architecture Build real-time dashboards with actionable insights Develop predictive models for: Volume forecasting Churn risk SLA breach risk Escalation likelihood Transform support data into a strategic asset 6. Platform & Architecture Ownership Own the support technology stack end-to-end Ensure integration with Sales, Customer Success, Billing, and Product systems Standardize APIs and data models to support AI trainin