CKEditor

Revenue Operations

• Design the revenue engine architecture and end-to-end customer journey across self-service and sales-assisted motions
• Define segmentation, coverage, routing, lifecycle stages and cross-functional handoffs
• Lead sales, customer success and partner operations across all Tiugo brands
• Design territory coverage, quota setting, capacity and productivity models, and forecast processes
• Design incentive plans while partnering with Finance on administration and payouts
• Build and define the deal desk function for enterprise and AI deals
• Support deal structure, pricing, quoting, and legal, finance and security reviews
• Build field enablement covering onboarding, ramp, sales methodology, and product and AI fluency
• Hire the field enablement leader
• Own go-to-market engineering, revenue-organization automation and internal AI applications
• Analyze revenue performance, diagnose changes, and provide actionable recommendations
• Partner with Sales & CS, Data & Analytics, AI, Marketing, Finance, Product and Engineering teams
• Establish coverage, segmentation and routing across brands
• Improve forecast accuracy and deal desk effectiveness
• Automate revenue work and reduce manual effort for sellers

Explore Head of Revenue Operations at CKEditor. Review requirements and application details.

Head of Revenue Operations

Solutions Engineer

• Lead the technical side of complex deals, mainly TinyMCE AI and strategic enterprise opportunities for the core editor
• Work alongside Account Executives, Account Managers, and Product Managers
• Lead technical discovery across customer architecture, content workflows, integration requirements, and AI ambitions
• Act as a trusted technical advisor and help customers evaluate architecture choices
• Deliver tailored, use-case-driven demos
• Own the technical win from discovery through architecture, security review, and sign-off
• Translate technical capabilities into business outcomes
• Establish evaluation criteria and lead disciplined POCs with defined success criteria, outcomes, timelines, and checkpoints
• Guide build-versus-buy and competitive evaluations
• Explain AI architecture, including user experience, orchestration, underlying models, LLM APIs, RAG, model choice, data privacy, and security
• Partner with AEs and AMs to turn technical differentiation into business cases
• Build reusable demo and discovery frameworks, POC processes, and competitive playbooks
• Provide structured customer and competitive feedback to Product and Engineering
• Enable AEs and AMs to handle first-level technical and AI discovery independently

Explore Solutions Engineer at CKEditor. Review requirements and application details.