Lead Product Manager - AI Solutions

Vertex Inc. is seeking a Lead Product Manager – AI Solutions to drive the definition and execution of AI-first and AI-enabled product capabilities. The role involves owning the end-to-end lifecycle for features and capabilities, collaborating with various teams to translate customer needs and technical possibilities into clear product requirements.

Responsibilities:

• Drive the definition and execution of AI-first and AI-enabled product capabilities within a defined product area
• Own the end-to-end lifecycle for features and capabilities, partnering closely with engineering, UX, tax research, security & governance, and go-to-market teams to translate customer needs, market insights, and technical possibilities into clear product requirements and delivered outcomes
• Contribute meaningfully to AI product strategy and roadmap execution by ensuring AI capabilities are customer-ready, continuously improving, and delivering measurable business impact
• Define clear product requirements for AI‑powered capabilities and AI‑enabled integrations, with explicit expectations for evaluation criteria, and feedback mechanisms built into the roadmap
• Partner closely with engineering teams on model evaluation, experimentation, and tuning, to identify opportunities for iterative improvements, and assess release readiness
• Drive the continuous evolution of AI features by identifying gaps through customer feedback, usage metrics, AI performance signals, and translating those insights into sequenced roadmap investments and delivery milestones
• Curate and maintain a capability‑level AI roadmap for assigned AI features and core capabilities, prioritizing incremental improvements that drive quality, trust and customer value
• Metrics-driven product delivery, including defining success metrics, assessing outcomes, and using findings to guide iteration
• Experience applying responsible AI principles, including traceability, privacy, security, bias awareness, transparency, and auditability within owned capabilities
• Clear, structured communication skills, conveying priorities, trade-offs, risks, and progress to cross-functional stakeholders
• Possess the technical acumen to experiment directly using AI tools for faster product prototyping
• Understand how modern AI systems and AI Agents behave, improve over time, and fail
• Understand how to use those characteristics to influence product decisions and user experience evolution
• Ability to create or curate representative mock or synthetic datasets to support experimentation, evaluation, and validation

Requirements:

• Minimum of 3 years of hands-on AI product experience commercially launching AI-driven and data-intensive product capabilities
• Define clear product requirements for AI‑powered capabilities and AI‑enabled integrations, with explicit expectations for evaluation criteria, and feedback mechanisms built into the roadmap
• Partner closely with engineering teams on model evaluation, experimentation, and tuning, to identify opportunities for iterative improvements, and assess release readiness
• Drive the continuous evolution of AI features by identifying gaps through customer feedback, usage metrics, AI performance signals, and translating those insights into sequenced roadmap investments and delivery milestones
• Curate and maintain a capability‑level AI roadmap for assigned AI features and core capabilities, prioritizing incremental improvements that drive quality, trust and customer value
• Metrics-driven product delivery, including defining success metrics, assessing outcomes, and using findings to guide iteration
• Experience applying responsible AI principles, including traceability, privacy, security, bias awareness, transparency, and auditability within owned capabilities
• Clear, structured communication skills, conveying priorities, trade-offs, risks, and progress to cross-functional stakeholders
• AI Fluency: this role requires practical, hands-on AI fluency. The ideal candidate will be comfortable operating directly in the AI product development lifecycle
• Possess the technical acumen to experiment directly using AI tools for faster product prototyping
• Understand how modern AI systems and AI Agents behave, improve over time, and fail
• Understand how to use those characteristics to influence product decisions and user experience evolution
• Ability to create or curate representative mock or synthetic datasets to support experimentation, evaluation, and validation
• Bachelor's degree in business, engineering, or a related field. Equivalent combination of education, training, and relevant professional experience accepted in lieu of a formal degree
• Some experience mentoring or coaching junior product owners on AI fluency and product development practices