Senior Director, Enterprise AI

7-Eleven is an iconic family of brands with over 86,000 locations, surpassing every retailer in the world. We revolutionize convenience, restaurants and fuel through cutting edge innovation — working hard to be the customer's first choice. 7-Eleven empowers our employees to "activate awesome" and make a meaningful impact in their stores and communities every day. If you're ready to grow, lead and make a difference, come join our team and help shape the future of convenience.

Job Overview

7-Eleven is on a multi-year journey to become an AI-first retailer — embedding intelligence into every store, every customer interaction, every enterprise decision, and every line of code we ship. We are seeking a Senior Director, Enterprise AI to lead the design, engineering, and scaling of the AI platforms that power that transformation.

This is a builder's leadership role. It combines AI strategy, product innovation, and hands-on engineering leadership, with end-to-end accountability for delivering production-grade AI systems across four frontiers: AI for Customer (Agentic Commerce), AI for Stores, AI for Enterprise, and AI for SDLC. You will own the roadmap from real-time, edge-based decisioning in stores to agentic, personalized commerce for millions of customers — while modernizing how 7-Eleven's own engineering organization builds software with AI.

The Four Pillars of 7-Eleven's AI Journey

1. AI for Customer — Agentic Commerce

Reimagine the customer experience around autonomous, intelligent agents that anticipate and act on customer needs.

• Build customer-facing AI: personalization, recommendations, conversational and agentic shopping experiences, and retail media.
• Deliver agentic commerce capabilities — AI agents that plan, decide, and complete tasks across mobile, loyalty, and digital channels on the customer's behalf.
• Drive data-driven, frictionless journeys that measurably improve satisfaction, engagement, and revenue per customer.

2. AI for Stores

Bring real-time intelligence to the edge — across thousands of stores.

• Deliver AI for intelligent store operations: inventory, labor, equipment uptime, loss prevention, and automation.
• Enable edge and real-time AI and computer vision for in-store decisioning where latency and reliability are critical.
• Integrate AI into core store systems (POS, supply chain, store apps) to improve speed, accuracy, and associate productivity.

3. AI for Enterprise

Embed AI into corporate decision-making and enterprise workflows.

• Scale high-impact GenAI and predictive use cases across merchandising, finance, supply chain, and corporate operations.
• Build enterprise knowledge, copilots, and automation that augment decision-making and reduce manual effort.
• Integrate AI capabilities into core enterprise platforms and data ecosystems.

4. AI for SDLC

Transform how 7-Eleven builds software with AI.

• Drive adoption of AI-assisted engineering — code generation, automated testing, code review, documentation, and DevOps automation.
• Establish platforms, standards, and guardrails that accelerate developer velocity and software quality across engineering teams.
• Measure and improve engineering throughput, cycle time, and quality through AI-augmented SDLC tooling.

Key Responsibilities

Strategy & Retail AI Innovation

• Define and execute a multi-year enterprise AI roadmap aligned to customer, store, enterprise, and engineering priorities.
• Identify and scale high-impact use cases across all four pillars.
• Translate emerging capabilities (GenAI, agentic AI, predictive analytics, computer vision) into practical, production retail solutions.

AI Engineering & Platform Delivery

• Own end-to-end AI engineering delivery: architecture → production → scale.
• Build and operate enterprise AI platforms — data pipelines, MLOps/LLMOps, real-time inference, agent orchestration, and GenAI tooling.
• Enable edge and real-time AI for in-store and customer-facing applications.
• Integrate AI into core systems (POS, mobile, loyalty, supply chain, enterprise platforms).
• Establish standards for scalability, reliability, and performance.

Operational Impact & Scale

• Scale AI across thousands of stores and millions of customer interactions.
• Drive measurable outcomes across revenue, efficiency, and productivity.
• Establish KPIs for adoption, performance, and ROI across each pillar.

Governance & Risk

• Implement responsible AI frameworks covering risk, compliance, data privacy, and security.