Director, AI Commercial Product Strategy

Overview

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

This role requires a strong communicator capable of lead ing discovery conversations, engag ing confidently with clients and executive stakeholders, synthesiz ing ambiguous information, and turn ing complex capabilities into clear business recommendations.

The role considers market intelligence, partner capabilities, client feedback, competitive insights, solution messaging, and ROI models into a coherent commercialization message .

This Director works across Sales and Client Services , AI Technology Partners, Marketing, and the Wave iX team to ensure solution offer ings evolve to meet client needs and opportunities.

This role works alongside internal Sales and CS, and is a counterpart to the AI technology partners’ account teams, including Account Executives and Solutions Engineering. It translates partner product roadmaps and proof - points 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. This Director will ensure that the commercial organization knows what to sell, why clients buy it, how to differentiate it, and how to build a credible business case.

Responsibilities

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:

Document and maintain the inventory of AI Agents per vertical and use case.

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 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. 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.

4. 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.

Success Measures (KPIs)

Revenue and Commercial Impact

AI Agent revenue.

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.

Sales satisfaction.

Solution team satisfaction.

Qualifications

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.

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 sales, marketing, 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.

Core Competencies

Commercial judgment and consultative selling.

Executive and client communication.

Critical thinking and structured problem solving.

Strategic thinking and prioritization.

Product marketing and go-to-market strategy.

Persuasive storytelling and presentation.

AI and CX domain expertise .

Ability to translate technical capabilities into business outcomes.

Financial and ROI modeling.

Cross-functional leadership and influence without authority.

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:

Document and maintain the inventory of AI Agents per vertical and use case.

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 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. 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.

4. 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.

Success Measures (KPIs)

Revenue and Commercial Impact

AI Agent revenue.

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.

Sales 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.

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 sales, marketing, 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.

Core Competencies

Commercial judgment and consultative selling.

Executive and client communication.

Critical thinking and structured problem solving.

Strategic thinking and prioritization.

Product marketing and go-to-market strategy.

Persuasive storytelling and presentation.

AI and CX domain expertise .

Ability to translate technical capabilities into business outcomes.

Financial and ROI modeling.

Cross-functional leadership and influence without authority.