Senior Product Manager – AI Innovation

Overview

As a Senior Product Manager in the AI Innovation group, you will own the vision and strategy for AI-driven enhancements to Salsify’s core PXM platform. You’ll move ideas to shipped value, conduct discovery with customers and stakeholders, and collaborate with engineering and design to bring concepts to life. You will build credibility across Customer Success, Sales, Marketing, Solutions Advisory, Support, and R&D to ensure adoption. This role appeals to curious, execution-focused leaders who want to shape AI-powered product outcomes at scale.

Pay / Benefits

• Total Rewards plan
• health & medical benefits
• PTO
• base salary plus potential commission/bonus
• competitive compensation
• equitable pay relative to market

Responsibilities

• Set and champion the vision for your AI Innovation area aligned with business objectives
• Lead discovery with customers, partners, and internal stakeholders to uncover use cases and desired outcomes
• Use AI to accelerate signal collection alongside traditional discovery methods
• Hands-on AI work with LLMs, agents, and AI tools
• Run tight experiments and pilots with defined hypotheses and success metrics
• Collaborate with engineering manager and designer to run the trio effectively
• Maintain relationships across teams to align AI work with the organization
• Identify cross-team synergies and proactively mitigate risks
• Communicate status, progress, and blockers to senior leaders and audiences
• Represent your product area internally and with customers
• Address disagreements constructively and build trust

Key requirements

• 5-8 years of product management experience or equivalent
• Strong product judgment to frame strategy and defend viewpoints
• Hands-on AI fluency with LLMs, agents, and AI tools
• Experience building AI products and scaling AI initiatives
• Experimental discipline with data-driven decision making
• Track record of leading discovery with technical audiences
• Ability to prioritize across competing time horizons and say no when needed
• Effective communication with engineering teams and business stakeholders
• History of delivering cross-team initiatives impacting company metrics
• Resilience and bias to action in ambiguous situations

• strong communication
• cross-functional collaboration
• ambition and curiosity
• LLMs, agents, and AI tools
• AI-driven product discovery and experimentation
• data-driven decision making

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