Lead Full Stack Software Engineer - AI Assisted Engineering Practices

Role Summary

The Lead Software Engineer will lead 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.

What You’ll Do

• 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 TypeScript; 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
• Design, implement, and review APIs, microservices, and backend integrations supporting business and guest experiences
• 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)
• 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
• 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 estimation, planning, and delivery of complex initiatives
• Ensure CI/CD, monitoring, logging, and observability are built into all solutions
• Review and approve solution designs and technical documentation
• Ensure you remain up to date with emerging technologies so you can make informed recommendations

Required Qualifications

• 7+ years of professional software engineering experience
• Demonstrated ability to lead technical decision-making, influence architecture across teams, and align engineering solutions with business outcomes
• An advocate for a diverse and inclusive culture that encourages innovation and ensures every team member feels a sense of belonging
• Must have demonstrated success using AI coding assistants (agentic IDEs / AI pair programming) to improve delivery speed and quality
• Must have experience implementing AI-enabled automation across SDLC (testing, code review, documentation, CI/CD) with measurable outcomes
• Strong “trust-but-verify” discipline: validate, secure, refactor, and govern AI-generated output to meet maintainability standards
• Absolutely must have experience with Node.js, React and Angular in large-scale applications
• Must have solid full-stack experience with Java, Spring, Spring Boot, RESTful APIs, and microservices
• Experience designing and operating CI/CD pipelines
• Experience with monitoring and observability tools (e.g., Splunk, AppDynamics, etc.)
• Strong understanding of object-oriented design and software architecture principles
• Experience working in agile development environments

Preferred Qualifications

• 10+ years of experience building and supporting enterprise-scale, customer-facing platforms
• Experience with Adobe Experience Manager (AEM), including AEM as a Cloud Service
• Experience with headless or hybrid AEM architectures
• Experience using AI assisted development tools in large engineering teams
• Understanding of responsible AI principles in enterprise or consumer facing environments
• Experience with cloud-based technologies like AWS, Google Cloud, Microsoft Azure
• Experience with Confluence and Jira to document requirements, user stories and technical designs