Lead Product Manager

Vertex•King of Prussia, PA

23h

About The Position

The Lead Product Manager – AI Solutions role is a hands-on, individual contributor position that drives the definition and execution of AI-first and AI-enabled product capabilities within a defined product area. This position owns 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. The role contributes meaningfully to AI product strategy and roadmap execution by ensuring AI capabilities are customer-ready, continuously improving, and delivering measurable business impact.

Requirements

Minimum of 3 years of hands-on AI product experience commercially launching AI-driven and data-intensive product capabilities.
AI Fluency: practical, hands-on AI fluency.
Comfortable operating directly in the AI product development lifecycle.
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 AI 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.
Clear, structured communication skills.

Nice To Haves

Some experience mentoring or coaching junior product owners on AI fluency and product development practices.

Responsibilities

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.
Apply responsible AI principles, including traceability, privacy, security, bias awareness, transparency, and auditability within owned capabilities.
Communicate priorities, trade-offs, risks, and progress to cross-functional stakeholders.