Senior Product Manager 

At Innervate, we envision an “Innervated” future where marketing professionals seamlessly orchestrate personalized, dynamic content—for any channel—without today’s high costs and the headaches caused by siloed systems and data. 

We help companies automatically deliver the right content, in the right place, at the right time. Instead of teams manually creating endless versions of creatives, Innervate connects data, creative, and channels so content can adapt itself in real time. 

We are now in the middle of a significant platform evolution: rebuilding our Dynamic Content Orchestration Platform around an AI Agentic architecture. This is not a future roadmap item — it’s happening now, and this role sits at the center of it. 

About the Role

We’re looking for a deeply analytical and customer-centric Senior Product Manager to join our Product team. This is not a role for someone who wants to observe the AI transformation of marketing technology — it’s for someone who wants to build it. 

You’ll serve as the bridge between customers and our product organization, ensuring that everything we build is grounded in real-world needs and strategic business value. That means navigating a platform in active transformation: handling large volumes of customer signals, market data, and internal context simultaneously and synthesizing it into a clear product direction. 

You have hands-on experience with AI UX patterns—not just as a user, but as someone who has thought through how agentic systems should feel, where automation earns trust, and where human control must remain explicit. You understand the difference between a well-designed AI workflow and one that collapses under real-world complexity. 

This role requires someone who can hold two things at once: extending a production platform that customers depend on today while actively shaping what that platform becomes as we introduce agentic capabilities across orchestration, personalization, and content delivery. 

What you will do:

Customer and Stakeholder Engagement 

• Lead customer-facing discovery sessions and requirement-gathering interviews, with a specific focus on surfacing how customers currently handle—or struggle with—high-volume content decisions that are candidates for AI automation.
  
  
• Collaborate with Customer Success, Technical Account Management, and Sales Engineering to unify feedback at scale, building repeatable intake structures rather than ad hoc synthesis.
  
  
• Help customers navigate the shift from manual content orchestration to AI-assisted workflows, setting accurate expectations about agentic capabilities and their limits.

Requirements Gathering & Synthesis at Scale

• Ingest and manage large, continuous streams of feedback across customers, internal teams, support queues, and market signals—and distill them into prioritized, structured product documentation.
  
  
• Go beyond traditional PRDs: capture the tradeoffs, constraints, and context behind each product decision, including where AI-generated outputs require human review versus where full automation is appropriate. 
  
  
• Build internal artifacts that give engineering, QA, and UX teams enough context to make good decisions independently, reducing the need for constant PM involvement in implementation details. 
  
  
• Prioritize based on both customer urgency and platform coherence — especially where new agentic features could conflict with or destabilize existing functionality. 

AI UX Pattern Ownership 

• Define and document AI interaction patterns for our platform: how users initiate, monitor, override, and audit agent-driven workflows across content orchestration, audience targeting, and dynamic delivery.
  
  
• Distinguish clearly between automation that should run silently, automation that requires confirmation, and decisions that must remain with the human operator—and ensure those distinctions are reflected in product specs.
  
  
• Work with UX/UI to design interfaces that make AI behavior legible: surfacing confidence levels, explaining content decisions, and giving users appropriate control without overwhelming them with complexity.
  
  
• Identify failure modes in agentic workflows early—edge cases, data gaps, conflicting rules—and design guardrails before they become customer-facing issues.

Platform Transformation Stewardship

• Maintain a clear map of existing platform capabilities and their dependencies so that AI-driven additions enhance rather than disrupt what customers rely on today.
  
  
• Sequence feature development so that agentic capabilities are introduced incrementally and reversibly, with rollback paths and human override always available.
  
  
• Communicate the transformation roadmap internally and externally with honesty: what is built, what is in progress, and what remains speculative.

Market Research & Product Instrumentation

• Conduct and internalize research on AI UX trends in AdTech/MarTech, with a focus on how competitors and adjacent platforms are approaching agentic content automation.
  
  
• Define instrumentation requirements for AI-driven features: what signals indicate the agent is working, what indicates degradation, and what triggers escalation to human review.
  
  
• Synthesize usage data, customer behavior, and market signals into product decisions that balance innovation with platform stability.
  
  

Cross-Functional Collaboration

• Work closely with Engineering to pressure-test AI feature feasibility, surface model limitations early, and sequence work so that agentic capabilities are introduced on a foundation that can support them.
  
  
• Ensure QA teams understand not just functional requirements but the specific ways AI-generated outputs can fail silently, and design test coverage accordingly.
  
  
• Partner with UX/UI to align agent-driven workflows with customer mental models, making complex orchestration feel controllable and understandable.
  
  
• Coordinate with Program/Project Management to sequence platform transformation work alongside ongoing customer commitments.

About you: 

Domain Expertise 

• 5+ years in AdTech/MarTech SaaS, with deep knowledge of marketing technology stacks, digital marketing workflows, and dynamic content delivery.
  
  
• Direct experience designing or shipping AI-assisted features in a production environment — not just familiarity with AI tools as an end user.
  
  
• Practical understanding of AI UX patterns: progressive disclosure, human-in-the-loop confirmation flows, explainability interfaces, confidence scoring, and agent monitoring dashboards.
  
  
  

Information Management at Scale

• Demonstrated ability to ingest high volumes of ambiguous, sometimes conflicting input—from customers, internal teams, data systems, and market signals—and produce structured, prioritized output from it.
  
  
• Strong documentation instincts: you write things down in ways that reduce future questions, not just capture current decisions.
  
  
• Comfort operating in a context-switching environment where multiple workstreams, customer escalations, and platform decisions are active simultaneously.
  
  

Platform Transformation Experience

• Experience shipping product on a platform undergoing significant architectural change, where servicing existing customers and building new capabilities had to be managed in parallel.
  
  
• Judgment about when to extend existing patterns versus when to introduce a new paradigm — and how to communicate that choice to both technical and non-technical stakeholders.
  
  

Communication Excellence

• Verbal: Ability to lead strategic conversations with executive stakeholders, run technical discovery sessions with end-users, and explain AI system behavior to non-technical audiences without oversimplifying.
• Written: Mastery in documenting requirements, articulating tradeoffs, and producing artifacts that engineering, QA, and UX teams can act on independently.
  
  

Analytical & Problem-Solving

• Ability to break down ambiguous, AI-adjacent requirements into structured, testable statements that account for non-deterministic outputs.
  
  
• Comfortable using both qualitative feedback and quantitative usage data to inform product decisions, including data generated by AI systems themselves.
  
  

Business Acumen & Customer Empathy 

• Deep understanding of business models, revenue drivers, and customer ROI in a dynamic content context.
• Ability to represent the customer’s perspective when evaluating AI-driven automation — including when a proposed agent behavior would erode trust or control even if it improves performance metrics.
  
  

Business Acumen & Customer Empathy

• Ability to connect immediate customer requirements to long-term platform direction, particularly as that direction moves toward agentic orchestration.
  
  
• Demonstrated experience navigating the tension between shipping incrementally and building toward a coherent architectural future.

How to Apply

Feels like a match? Send your pitch and resume to careers@innervate.com.