Product Manager - AI Agents

The Product Manager for AI Agents is responsible for ensuring the AI Agent product achieves product-market fit and can be successfully sold, positioned, and scaled across ibex.

This role serves as the commercial owner of the product, bringing together market intelligence, partner capabilities, client feedback, competitive insights, solution messaging, ROI models, sales enablement, and knowledge management into a single commercialization strategy.

The Product Manager works across Product Partners, Sales, Marketing, Wave iX Solutions, Operations, and Technology to ensure the product evolves in response to both market demand and operational realities. This role is also the primary commercial counterpart to the platform partners’ account teams (Account Executive and Solutions Engineering), responsible for translating the partners’ product roadmaps and proof points into ibex-branded commercial assets, and for identifying co-selling opportunities.

This role does not own engineering, implementation, or delivery. Instead, it supports the SVP, Wave iX Commercial in ensuring that the commercial organization always knows what to sell, why clients buy it, how to differentiate it, and how to position ibex as the enterprise AI operating partner.

• Commercial Strategy - own the commercial strategy for the AI Agent product at ibex.
  • Monitor AI Agent market trends
  • Identify emerging customer needs
  • Evaluate competitive positioning
  • Recommend new commercial offerings
  • Define target industries and use cases
  • Maintain the commercial roadmap for AI Agents
• Maintain and expand the vertical playbook (currently five verticals: software/high-tech, healthcare, fintech, retail/e-commerce, telco) in partnership with the platform partner's account team, including new verticals as demand emerges
• Market Intelligence - become ibex's internal expert on the AI Agent marketplace.
  • Competitor analysis
  • Platform product comparisons
  • Industry trends
  • Analyst research
  • Client feedback
  • Win/loss analysis
  • Quarterly market updates
  • Competitive battle cards to educate internal sellers
  • Executive briefs
  • Opportunity assessments
• Use Case Development - develop repeatable AI Agent use cases.
  • Conversational IVR, replacing press menu IVRs
  • Call spikes
  • Seasonality
  • Low-complexity, high-volume interactions
  • Agent-facing copilot for Internal Knowledge lookup
  • Multi-channel identity and account unification
  • Business challenge, AI solution, Client value, ROI, KPIs, Reference architecture, Required integrations, Success stories
  • Each use case should reference existing proof points (e.g. cost reduction and resolution-rate benchmarks from live customer deployments) so reps are not building ROI narratives from scratch per deal.
• Value Proposition & Messaging - own product messaging.
  • Value propositions
  • Elevator pitches
  • Executive presentations
  • Differentiators
  • Objection handling
  • Industry messaging
  • Partner positioning

  Ensure consistent messaging across Sales, Marketing, Client Success, and Executive Leadership. Maintain a clear internal delineation between white label-safe messaging (client-facing, no vendor names) and partner-facing technical detail (internal only), ensuring reps never inadvertently disclose the underlying platform partnership in client conversations, proposals, or RFP responses. Own the objection-handling FAQ as a living asset, continuously updated rather than treated as a one-time deliverable.

• Sales Enablement - create commercial assets that accelerate revenue.
  • Sales playbooks
  • Discovery guides
  • Qualification guides
  • ROI calculators
  • Proposal content
  • Battlecards
  • Demo scripts
  • Executive presentations
  • Customer references

  Measure adoption and continuously improve these assets. Own and continuously refine the demo sequencing playbook based on live deal feedback (e.g. leading with…