Director – AI & Data Strategy; Retail Transformation; Phoenix, Arizona

Job Description

The Director, AI Practice & Transformation is the senior Intellibus leader responsible for guiding a top U.S. retailer’s executive team through its next-generation AI transformation and building out the Retail BU for Intellibus - including setting up the core team and scaling it globally to delivery for the current and new clients.

This role sits at the intersection of industry strategy, technology, and execution — ensuring that every AI and data initiative delivers measurable business impact.

The Director will partner directly with the client’s Executive Leadership Team (ELT) to translate strategic goals into actionable AI programs, oversee delivery across multiple squads (AI Skunk Works, Data Foundations, and Engineering Excellence), and ensure alignment with the client’s values, governance principles, and operational realities. Director will also partner with the internal support and operations team to identify support areas and enable them for client success.

This is a hands‑on leadership role for someone who has both executive presence, domain depth and technical fluency comfortable in the boardroom and the data room.

• Serve as the primary Intellibus liaison to the client’s ELT and senior leadership.
• Translate strategic priorities into a portfolio of AI and data initiatives aligned to revenue, productivity, and customer‑experience goals.
• Lead monthly AI Practice reviews with the ELT — reporting progress, learnings, and value realization.
• Ensure all work aligns with the client’s “AI Guardrails” and ethical use principles.
• Act as the “voice of reality” to the ELT — balancing ambition with feasibility

• Oversee delivery across three major work streams:
  (a) AI Skunk Works Experiments — rapid 2‑week pilots that prove business value.
  (b) Data Foundations — building the AI substrate: clean, connected, governed data.
  (c) Engineering Excellence — upskilling the client’s tech organization for velocity and reliability.
• Coordinate the work of ~20 engineers and leads across Intellibus and client teams.
• Manage the overall execution plan, sprint cadence, and dependency resolution.
• Track KPIs for time‑to‑value, productivity improvement, and financial impact.
• Ensure cross‑squad integration — AI pilots, data, and engineering improvements reinforce each other.

• Provide architectural and technical oversight for AI pilots and data integration efforts.
• Guide AI experimentation design — from problem framing to success measurement.
• Advise on the selection and evaluation of AI platforms, cloud infrastructure, and data frameworks.
• Understand retail systems (POS, loyalty, supply chain, merchandising) and how AI can enhance them.
• Actively review and approve key technical deliverables to ensure quality and coherence.

• Build trusted relationships with ELT members, department heads, and technical leaders.
• Mentor squad leads (AI, Data, Engineering) and ensure consistent methodologies across work streams.
• Foster a culture of experimentation, transparency, and measurable impact.
• Support the AI & Data Strategy Lead (ELT Liaison) in framing use cases, KPIs, and data‑readiness insights.
• Represent Intellibus’ principles of “Engineering Excellence” and ethical, human‑centered AI.
• Establish an operating cadence for reporting: weekly squad syncs, bi‑weekly sprint reviews, monthly ELT checkpoint.
• Deliver dashboards and executive summaries quantifying business value (e.g., cost savings, time reduction, revenue lift).
• Publish quarterly “AI Practice Report” summarizing progress, lessons, and roadmap adjustments.
• Drive continuous improvement through structured retrospectives and guardrail updates.
• 90‑Day AI Practice Plan with measurable milestones.
• Three active AI experiments with ELT sponsorship and quantified KPIs.
• AI Practice Charter (governance, operating model, ethical guidelines).
• Monthly executive dashboard summarizing AI outcomes and ROI.
• Engineering Excellence uplift metrics (velocity, stability, automation improvements).

• Experience:
  
  12–20 years in technology, AI, or digital transformation; at least 5 years in…