The Senior Engineering Manager, Personalization & Web Properties leads the engineering organization responsible for 7-Eleven’s personalization, decisioning, web experience, and supporting marketing technology capabilities.

This role owns end-to-end engineering execution across platforms and services that deliver relevant customer experiences across web, app, CRM, in-store, pump, and other omnichannel touchpoints. The role provides technical leadership for personalization and decisioning, data integrations, hot-path and cold-path processing, web front-end platforms, CMS, digital asset management (DAM), workflow tools, experimentation, and experience delivery.

The Senior Engineering Manager partners closely with Marketing Technology, Product, Marketing, Data & Analytics, Architecture, Security, and Enterprise Platforms. The role is accountable for establishing strong engineering practices, reliable data and platform foundations, scalable architecture, production operations, and measurable delivery outcomes.

The successful candidate is a strong people leader and hands-on technical strategist who has led complex engineering initiatives from strategy and architecture through production. The role will also guide the responsible adoption of AI coding tools and the design, deployment, and operation of AI agents in production.

KEY DUTIES AND RESPONSIBILITIES

• Lead and manage engineering teams responsible for personalization, decisioning, web properties, and supporting MarTech platforms.
• Own the engineering roadmap, delivery strategy, architecture direction, prioritization, and operating cadence for the portfolio.
• Lead execution end to end, including discovery, technical design, development, testing, release, observability, incident response, and continuous improvement.
• Establish strong engineering principles covering modular architecture, API-first design, automated testing, CI/CD, security, reliability, observability, and operational readiness.
• Design and evolve omnichannel personalization capabilities across web, app, CRM, in-store, pump, paid media, and other customer touchpoints.
• Guide decisioning capabilities, including rules, eligibility, segmentation, recommendations, experimentation, next-best-action, and offer selection.
• Define effective hot-path and cold-path data architectures that balance latency, freshness, scalability, reliability, cost, and governance.
• Partner with data and platform teams to establish trusted data sources, data contracts, event and profile schemas, lineage, quality controls, privacy safeguards, and monitoring.
• Lead engineering integration with marketing technology and data platforms, including Databricks, Hightouch, customer data sources, identity/profile services, experimentation platforms, and activation channels.
• Provide technical direction for web front-end architecture and integrations across CMS, DAM, workflow, content governance, publishing, and digital experience delivery platforms.
• Improve web property performance, accessibility, security, SEO, experimentation, availability, developer experience, and operational visibility.
• Evaluate and integrate commercial and open-platform personalization technologies while maintaining a pragmatic, extensible architecture.
• Build, coach, and retain a high-performing engineering organization; establish role clarity, career development, succession planning, and accountability.
• Manage hiring, performance management, delivery commitments, technical risk, dependencies, vendor relationships, and stakeholder communication.
• Establish a practical strategy for AI-assisted software engineering, including adoption of AI coding tools to improve productivity, quality, testing, documentation, and developer experience.
• Lead the build and deployment of AI agents in production, including agent workflows, tool integrations, evaluation, guardrails, observability, security, and human-in-the-loop controls.
• Partner with Security, Privacy, Legal, Architecture, and Risk teams to ensure responsible use of AI, customer data, and personalization technologies.
• Communicate complex technical concepts, tradeoffs, risks, and business impact clearly to technical, business, and executive audiences.

EDUCATION AND EXPERIENCE

• Education: Bachelor’s degree in computer science, Engineering, or a related field; equivalent practical experience may be considered.
• Years of relevant work experience: 10+ years.
• Years of management experience: 5+ years, including leadership of managers and/or multiple engineering teams.
• Certifications / licenses: None required. Agile, PMP, cloud, architecture, data, or AI-related certifications are a plus.

SPECIFIC KNOWLEDGE AND SKILLS

• Strong people leadership skills, including hiring, coaching, performance management, organizational design, and delivery leadership.
• Demonstrated success leading complex engineering execution from strategy and architecture through production operations.
• Deep understanding of personalization, decisioning, customer data, experimentation, recommendations, segmentation, next-best-action, and omnichannel activation.
• Strong engineering foundation in distributed systems, APIs, event-driven architecture, data-intensive systems, cloud-native platforms, and production reliability.
• Experience designing hot-path and cold-path data flows, data contracts, source-of-truth patterns, data quality controls, lineage, and observability.
• Familiarity with Databricks, Hightouch, identity and profile services, customer data platforms, marketing automation, experimentation, and activation technologies.
• Experience with modern web front-end architecture and CMS, DAM, workflow, content delivery, and digital experience management platforms.
• Experience integrating and operating personalization, decisioning, marketing technology, web, and data platforms at meaningful scale.
• Hands-on familiarity with AI coding tools and experience building, deploying, evaluating, securing, and operating AI agents in production.
• Understanding of security, privacy, consent, opt-in requirements, CCPA, data governance, and responsible AI practices.
• Strong vendor-management, roadmap-planning, prioritization, and cross-functional collaboration skills.
• Excellent communication and stakeholder-management skills across technical, business, and executive audiences.
• Experience in retail, convenience, e-commerce, loyalty, consumer technology, or another high-volume customer-facing environment is preferred.

This job description is intended to describe the general nature and level of the work being performed by the individuals assigned to this job. This is not an exhaustive list of all duties and responsibilities. Management reserves the right to amend and change the duties and responsibilities of this job to meet business and organizational needs, as necessary

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