Director, AI Commercial Product Strategy

Reporting to and supporting the SVP of Wave iX, The Director of AI Commercial Product Strategy is responsible for turning AI Agent capabilities into compelling, differentiated, and sellable solutions that create measurable value for clients and revenue for ibex.

This role is highly collaborative and externally oriented. It requires a strong communicator who can lead discovery conversations, engage confidently with client and executive stakeholders, ask incisive questions, challenge assumptions, synthesize ambiguous information, and turn complex capabilities into clear business recommendations. The Director works across Product Partners, Sales, Marketing, Wave iX Solutions, Operations, and Technology to shape the offer, support strategic pursuits, and ensure the product evolves in response to market demand, client needs, and operational realities.

This role is also the primary commercial counterpart to the platform partners’ account teams, including Account Executives and Solutions Engineering. It translates partner product roadmaps and proofpoints into ibex-branded commercial assets, identifies co-selling opportunities, and helps ibex teams win and expand business.

This role does not own engineering, implementation, or delivery. Technical fluency is important, but coding or engineering ownership is not required.

1. Commercial Strategy and Go-to-Market

Support the SVP of Wave iX with the commercial strategy and go-to-market plan for the AI Agent product at ibex.

Responsibilities include:

• Monitor AI Agent market trends and identify the implications for ibex.
• Identify emerging customer needs and translate them into prioritized commercial opportunities.
• Evaluate competitive positioning and recommend how ibex should win.
• Recommend new commercial offerings, packaging, and routes to market.
• Define target industries, buyer personas, and priority use cases.
• Maintain the commercial roadmap for AI Agents.
• Maintain and expand the vertical playbook, currently covering software/high-tech, healthcare, fintech, retail/e-commerce, and telco, in partnership with the platform partner’s account team.
• Help sales teams distinguish high-potential opportunities from poor-fit use cases and focus effort where ibex can create differentiated value.

2. Client Discovery, Critical Thinking, and Use Case Development

Lead the development of repeatable AI Agent use cases grounded in real customer problems, buying priorities, operational constraints, and measurable outcomes.

Examples include:

• Conversational IVR replacing press-menu IVRs.
• Call-spike and seasonality management.
• Low-complexity, high-volume interactions.
• Agent-facing copilots for internal knowledge lookup.
• Multi-channel identity and account unification.

The role will likely participate in or lead:

• Client discovery calls and executive working sessions.
• Use-case qualification and prioritization.
• Business-value and ROI workshops.
• Deal strategy sessions with Sales and Solutions teams.
• Structured evaluation of assumptions, risks, dependencies, and expected outcomes.

Each use case includes:

• Business challenge
• AI solution
• Client value
• ROI and financial assumptions
• KPIs
• Reference architecture
• Required integrations
• Success stories and proof points

Each use case should reference existing proof points, such as cost-reduction and resolution-rate benchmarks from live customer deployments, so representatives are not building ROI narratives from scratch for every deal.

3. Market Intelligence and Strategic Analysis

Become an internal expert on the AI Agent marketplace and turn market information into clear commercial decisions.

This includes:

• Relevant market analysis
• Platform product comparisons
• Industry trends
• Client feedback
• Win/loss analysis
• Clear recommendations that explain what the information means for product priorities, positioning, pipeline, and investment.

Outputs include:

• Quarterly market updates
• Competitive battlecards to educate internal sellers
• Executive briefs
• Opportunity assessments
• Decision memos for ambiguous or high-impact commercial questions.

4. Value Proposition, Messaging, and Executive Communication

Serve as a compelling storyteller for the AI Agent offer.

Develop and maintain:

• Value propositions
• Elevator pitches
• Executive presentations
• Differentiators
• Objection handling
• Industry messaging
• Partner positioning

Present and adapt the story for different audiences, including prospects, clients, executive leaders, Sales, Marketing, Operations, Solutions, and technology partners. Make the business case clear without oversimplifying the underlying product realities.

Ensure consistent messaging across Sales, Marketing, Client Success, and Executive Leadership.

5. Sales Enablement and Strategic Deal Support

Create commercial assets and provide hands-on support that accelerate revenue and improve seller confidence.

Examples include:

• Sales playbooks.
• Discovery guides.
• Qualification guides.
• ROI calculators.
• Proposal content.
• Demo scripts.
• Executive presentations.
• Customer references.

Support priority opportunities directly through discovery preparation, value proposition development, business-case creation, objection handling, executive meeting preparation, RFP responses, and deal reviews.

Measure adoption and continuously improve these assets using seller feedback, client feedback, win/loss insights, and pipeline outcomes.

Own and continuously refine the demo sequencing playbook based on live deal feedback, including lessons such as leading with lower-risk, non-revenue intents before higher-stakes automation when appropriate.

6. Partner Commercial Management

Work with strategic technology partners, including AI platform providers, on:

• Joint GTM planning.
• Co-selling programs.
• Sales enablement.
• Executive relationship support.
• Marketing coordination.
• Partner business reviews.
• Pipeline development.
• A standing joint pipeline review with the platform partner’s account team, at minimum monthly, covering active deals, deal stage, and enablement gaps.
• Serving as the primary escalation point for deal-specific support requests from partners, such as custom demos and ROI model builds, rather than routing these ad hoc through individual account relationships.

Build trusted relationships with partner Account Executives and Solutions Engineering teams and use those relationships to create joint client value, improve deal velocity, and identify co-selling opportunities.

Coordinate closely with Digital Transformation team for technical and operational partner management.

7. Cross-Functional Leadership

Serve as the commercial hub across Sales, Marketing, Wave iX Solutions, Operations. Technology, and Strategic Partners.

Create alignment through clear communication, sound judgment, and timely decisions. Surface trade-offs early, resolve ambiguity, and ensure stakeholders understand both the recommendation and the rationale behind it.

Ensure commercial commitments remain aligned with delivery capabilities, including coordination with the platform partner’s Solutions Engineering team for deal-specific technical scoping such as custom demo builds and proof-of-concept frameworks.

Success Measures (KPIs)

Revenue and Commercial Impact

• AI Agent revenue.
• Attach rate of AI Agent capability on new-logo deals.
• Average deal-size uplift when AI Agent capability is included.
• Pipeline created or influenced.

Client and Seller Adoption

• Asset adoption.
• Seller confidence and satisfaction.

Commercial Quality and Cross-Functional Effectiveness

• Quality and reuse of prioritized use cases.
• Accuracy and adoption of ROI models and proof points.
• Sales satisfaction.
• Partner satisfaction.
• Solution team satisfaction.

• Bachelor’s degree in business, finance, marketing, operations, or a related field, or equivalent practical experience.
• 7–10+ years in enterprise software, AI, SaaS, consulting, CX technology, product marketing, solutions consulting, partnerships, enterprise sales, or a commercially oriented product role.
• A meaningful track record in a customer-facing or revenue-oriented role, such as enterprise sales, sales engineering, solutions consulting, product marketing, go-to-market, partnerships, or commercial product management.
• Experience with conversational AI, virtual agents, contact center technologies, or customer experience transformation.
• Strong understanding of enterprise sales cycles, buying committees, qualification, business cases, and expansion motions.
• Demonstrated ability to lead client discovery, conduct executive presentations, facilitate workshops, and influence decisions without direct authority.
• Experience creating GTM strategies and sales enablement.
• Ability to translate technical capabilities into business outcomes, financial value, and a compelling client narrative.
• Strong critical-thinking and structured problem-solving skills, including the ability to assess incomplete information, test assumptions, prioritize opportunities, and make clear recommendations.
• Executive presentation and storytelling skills.
• Experience working across product, engineering, sales, operations, and executive stakeholders.
• Technical fluency sufficient to work effectively with product, technology, and Solutions Engineering teams; hands-on coding or engineering experience is not required.