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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Director, Enterprise AI - **Company:** 7-Eleven, Inc. - **Location:** Irving, TX, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Computer Vision, Automation of Tests, Microsoft Azure, Code Generation, Software Quality, Code Review, Machine Learning, Uptime, Systems Development Life Cycle, Software Engineering, Google Cloud, Cloud Platform System, AI Platforms, Deployment Automation, Data Analytics, Data Management, Machine Learning Operations, Virtual Agents, Data Pipelines - **Published:** July 4, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=22a58051ac73ca94 ## About the Role * 12-15+ years in AI/ML engineering, data platforms, or advanced analytics, with proven delivery at scale. * Strong track record building production AI systems and platforms - including GenAI and agentic AI. * Deep knowledge of ML, GenAI, MLOps/LLMOps, and cloud ecosystems (Azure, AWS, GCP). * Experience with AI-assisted software development and modern SDLC tooling. * Retail, multi-site, or customer-centric environment experience preferred. * Ability to operate as both a hands-on technologist and a strategic leader. ## Description 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., 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. * Ensure enterprise-grade governance across all AI systems and agents. Leadership & Influence * Build and lead a high-performing AI engineering organization. * Partner across IT, Digital, Product, and Operations to drive adoption. * Influence executive stakeholders and embed AI into core business strategy. ## Related Videos - [This App Reached 10,000 Users in One Week. Here's How.](https://www.wearedevelopers.com/videos/100329-this-app-reached-10-000-users-in-one-week-here-s-how) - [DevOps at Netflix](https://www.wearedevelopers.com/videos/270-devops-at-netflix) - [Are Code Reviews Worth It? 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