Lead Full Stack Software Engineer - AI Assisted Engineering Practices

Job Summary:

This is not a remote role. You must be in the area or willing to relocate!

"We Power the Magic!" That's our motto at Disney Experiences (DX). Our team creates world-class immersive digital experiences for the Company's premier vacation brands including Disney's Parks & Resorts worldwide, Disney Cruise Line, Disney Vacation Club, Storyliving by Disney, Adventures by Disney, and National Geographic Expeditions.

This role sits in the Disney Signature Experience organization within Technology & Digital for Disney Experiences. It supports high-visibility, guest-facing digital platforms and works closely with Storyliving by Disney, Adventures by Disney and National Geographic Expeditions (A&E) businesses.

Role Summary

The Lead Software Engineer will be responsible for leading the development and implementation of custom and commercial software projects to power both cast and guest experiences. They will champion the use of AI-assisted development tools and process automation across the software development lifecycle (SDLC), driving measurable improvements in delivery speed, code quality, and operational efficiency.

This role intentionally blends active software development with technical leadership. You will spend meaningful time designing, building, reviewing, and improving code while also setting technical direction, mentoring engineers, and guiding platform strategy. The role emphasizes modern front-end engineering (UI architecture, performance, accessibility, component-driven development) while maintaining full-stack responsibility with back-end systems.

You will partner closely with Product, UX, Content, and Business stakeholders to ensure the web platform and front-end ecosystem scale reliably to support best-in-class, high-traffic, revenue-generating digital experiences.

What You'll Do

Experience Platform & Front-End Engineering Leadership (Primary Focus)

* Own the technical strategy, roadmap, and operational health of the Adobe Experience Manager (AEM) platform and the guest-facing front-end ecosystem built on it

* Set front-end architecture direction for guest-facing web experiences (rendering strategy, component architecture, data/state patterns) and ensure consistency across products

* Lead platform upgrades, security posture, performance optimization, reliability, and scalability initiatives across both the platform and UI layer

* Establish and evolve engineering standards and best practices for front-end development (patterns, guardrails, quality gates, CI/CD expectations)

* Build and govern reusable capabilities: components/templates/workflows/content models and shared UI component libraries/design system adoption

* Write, review, and optimize production-quality code using JavaScript and Type Script; provide hands-on technical leadership for React and Angular implementations

* Champion web fundamentals using measurable standards and tooling: performance, accessibility (WCAG), SEO, and responsive design

* Partner with Product, UX, Design, and Content teams to translate designs into scalable, maintainable solutions and enable AI-assisted content workflows (e.g., tagging, summarization, optimization) with brand governance and quality controls

* Introduce AI-enhanced experience capabilities where valuable (e.g., intelligent search, recommendations, conversational interfaces, personalization) with appropriate quality and risk controls

Services & Integrations (Full-Stack Leadership)

* Design, implement, and review APIs, microservices, and backend integrations supporting business and guest experiences

* Define integration strategies with internal systems and third-party services, ensuring secure and reliable service contracts

* Contribute hands-on across the stack as needed to unblock teams, accelerate delivery, and resolve complex technical challenges

* Collaborate with architects on cloud-native and AI solution patterns, ensuring operability and maintainability

* Ensure end-to-end alignment between front-end, services, and infrastructure (performance, reliability, observability readiness)

Engineering Excellence & Delivery

* Drive adoption of AI-assisted engineering practices (agentic IDEs, code assistants, AI pair programming) to improve throughput and quality, with clear team guardrails and measurable outcomes

* Set standards for "trust-but-verify" usage of AI-generated code: validation, security review, refactoring expectations, and maintainability requirements (including preventing over-reliance on automation)

* Expand SDLC automation using AI where it improves outcomes (test generation, documentation generation, code review acceleration, pipeline improvements), while preserving engineering rigor

* Actively participate in development while leading code reviews to ensure quality, security, and maintainability

* Identify, prioritize, and remediate technical debt through hands-on contribution and backlog planning

* Translate business requirements into clear technical designs, stories, and implementation plans

* Guide…