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Define and execute the market strategy for UserTesting’s AI solutions. Own positioning, messaging, value propositions, go-to-market plans, sales enablement, customer and buyer research, competitive differentiation, thought leadership, and market feedback loops. Translate complex AI workflows and human-judgment applications into compelling solutions for technical enterprise buyers, while influencing product and company strategy through cross-functional leadership.

Serve as the primary post-sale value partner for a portfolio of customers, driving adoption and repeat usage of UserTesting. Advise on research best practices and methodology selection, translate research into practical guidance, support account planning and renewals, identify adoption risks, connect customers to internal teams, and maintain engagement documentation using tools like Planhat, Gong, and Salesforce.

Own end-to-end delivery of AI training projects, from customer scoping through execution. Develop contributor sourcing strategies, recruit and manage external communities, establish scalable workflows, monitor operational metrics, manage project economics, communicate with customers, and improve processes to support growth of UserTesting’s AI Training business.

Build and manage strategic partnerships and sales opportunities across the AI ecosystem. The role owns the full commercial process from outreach and discovery through solution development, negotiation, and close. It also develops repeatable partnerships, improves pipeline and forecasting operations, evaluates project feasibility, and contributes market insights to shape UserTesting’s emerging AI Training business.

Deploy and maintain AI enablement infrastructure (MCP servers, AI agents, AI features in SaaS), manage service accounts and API keys, automate and containerize services, support enterprise IT systems, document integrations and runbooks, and mentor IT support staff.

Lead strategy and execution for three domain websites: Webflow front-end development, SEO and AEO strategy, CRO experimentation, governance, analytics (GA4, Search Console), and cross-functional prioritization to improve traffic, engagement, and conversions.

Deploy and maintain AI enablement infrastructure (MCP servers, AI agents, hosting) and cloud environments on AWS/GCP. Build IaC and CI/CD pipelines, monitor performance/cost, support containerized services, manage API keys and permissions, document runbooks, and collaborate with Security, Engineering, and stakeholders to improve cloud governance and AI tooling adoption.