AI Digital Product Manager III

About the role

7‑Eleven is seeking an AI Product Manager III to own the end‑to‑end vision, strategy, roadmap, and adoption of AI‑powered products and capabilities across Customer, Store, Enterprise, Engineering, and Platforms. The role translates business priorities, associate and customer needs, and emerging AI capabilities into useful, trustworthy, scalable, and measurable products for the Store Support Center, customer experiences, and 7‑Eleven stores. It partners closely with data science, machine learning engineering, software engineering, design, operations, merchandising, legal, risk, and other enterprise stakeholders to move AI use cases from discovery through production and continuous improvement. Success is measured by business and user outcomes—including adoption, quality, accuracy, safety, efficiency, and realized value—not simply by features shipped.

Responsibilities

• Strategy & Planning (30%)
  • Identify and prioritize high‑value AI opportunities by understanding customer, associate, store, and enterprise needs and translating them into a clear product direction.
  • Define the AI product vision, roadmap, OKRs, and success measures; communicate priorities across product, design, data science, engineering, operations, and third‑party partners.
  • Establish outcome metrics and analytics for adoption, quality, accuracy, safety, efficiency, and business value; use evidence to refine the roadmap and backlog.
  • Assess data readiness, model or prompt feasibility, integration complexity, operational risks, and expected value to make informed prioritization and trade‑off decisions.
  • Monitor AI research, vendor capabilities, regulatory expectations, and the competitive landscape to identify emerging opportunities and recommend fit‑for‑purpose solutions.
  • Connect AI product decisions across upstream and downstream experiences to create coherent, explainable, and intuitive journeys for customers, associates, and operators.
• Delivery & Execution (50%)
  • Partner with research, design, data science, and engineering teams to formulate, test, and refine AI hypotheses through user research, prototyping, experimentation, and structured evaluation.
  • Translate AI product requirements into clear user stories, acceptance criteria, evaluation plans, and release milestones; drive sequencing decisions from discovery through production.
  • Make timely product decisions with minimal oversight, balancing user value, model performance, cost, latency, reliability, privacy, security, and responsible AI considerations.
  • Identify and resolve dependencies across data, models, prompts, APIs, platforms, vendors, governance, and operations; independently manage trade‑offs and escalate material risks.
  • Lead stand‑ups, iteration planning, product demos, model or prompt reviews, evaluation readouts, and retrospectives.
  • Explain complex AI, data, and technical concepts in clear business language so stakeholders can make informed decisions.
  • Drive quality documentation for product requirements, data and model assumptions, evaluation results, risks, decisions, launch plans, and operating procedures.
• Team & Stakeholder Collaboration (20%)
  • Build strong collaboration across products, UX, engineering, data science, machine learning, security, legal, risk, operations, and merchandising to deliver measurable value.
  • Advocate for customers, associates, and stakeholders while becoming the recognized product expert for the AI capability, its users, and its operating context.
  • Mentor junior product managers on AI product discovery, backlog management, evaluation planning, story writing, and stakeholder communication.
  • Communicate clearly at the appropriate level, translating AI strategy and responsible‑use principles into prioritized short‑term action and measurable outcomes.

Education and Experience

• Bachelor’s (4‑year) degree in business, computer science, engineering, information systems, data science, or a related field.
• 5+ years of relevant product management experience, including experience delivering AI, machine learning, automation, or data products.
• Preferred certifications in AI/ML, product management, cloud, or responsible AI (not required).

Specific Knowledge and Skills

• Human
  • Lead customer and associate research to understand workflows, trust needs, adoption barriers, and the appropriate role for AI.
  • Partner with design and research to create intuitive AI experiences and share learnings across teams.
  • Identify knowns, unknowns, assumptions, and failure modes; define learning plans to test AI product hypotheses.
  • Design and run qualitative and quantitative experiments, prototypes, and evaluations to measure usefulness, quality, safety, and adoption.
  • Synthesize voice‑of‑customer and voice‑of‑associate signals into prioritized AI product recommendations with clear action plans.
• Business
  • Execute business strategy by analyzing internal and external data to prioritize AI opportunities and make product decisions.
  • Build business cases independently and quantify expected and realized business impact of AI product changes.
  • Understand AI competition, market trends, vendor capabilities, and regulatory developments to influence the roadmap.
  • Develop data‑backed frameworks to measure AI quality, adoption, safety, efficiency, and business outcomes.
  • Solve ambiguous problems with tenacity, balancing speed, experimentation, quality, risk, and operational constraints.
• Technology
  • Demonstrate working knowledge of AI/ML product lifecycles, data pipelines, model and prompt evaluation, APIs, cloud platforms, privacy, security, and existing product architecture.
  • Understand when and how to apply machine learning, generative AI, retrieval, automation, analytics, microservices, and other technologies to solve business and user problems.
  • Partner with technology and data science to define and prioritize investments in data, models, platforms, tooling, monitoring, and integrations that drive customer and business benefit.
  • Provide product ownership by clearly articulating goals, requirements, evaluation criteria, and guardrails; lead planning, write and accept stories, and push for quality delivery.
• Transformation
  • Internalize the AI product vision and communicate it consistently across teams, including intended user value, limitations, risks, and responsible‑use expectations.
  • Demonstrate big‑picture thinking when sequencing discovery, data, model, platform, experience, and adoption work and making trade‑offs.
  • Lead product, design, AI/ML, and stakeholder reviews for the product area.
  • Tackle ambiguity independently and articulate AI product decisions, results, limitations, risks, and priorities effectively with stakeholders.
  • Seek multiple perspectives across the organization to connect dots, surface risks, and influence decisions.
  • Coach less experienced product managers on AI product management practices.

Position is onsite and based in Irving, TX. This role is not eligible for sponsorship.