Technical Strategy & Architectural Design
• Own the technical strategy and reference architecture for assigned accounts or practice areas, spanning Adobe Experience Cloud (AEC) components including Experience Platform, Real-Time CDP, Journey Optimizer, Content Management, GenStudio, and Analytics
• Lead discovery and assessment workshops to understand client business drivers, technical constraints, current-state platforms, data maturity, and content operation challenges; define target-state architectures that incorporate generative AI opportunities
• Design scalable, resilient solutions that balance functionality, performance, cost, and time-to-market; document architectural decisions and trade-offs clearly, including AI readiness and governance considerations
• Establish data governance, identity resolution, activation, personalization, and measurement frameworks tailored to client maturity and business objectives; assess opportunities for AI-driven decisioning and predictive insights
• Advise on platform selection, technology roadmapping, and make/buy decisions within the Adobe ecosystem and broader martech/data stack; include evaluation of GenStudio and Firefly capabilities for content workflows
• Design responsible AI guardrails and governance frameworks: model transparency, bias mitigation, compliance with regulatory requirements, and ethical AI practices
GenStudio, Firefly & Generative AI Integration
• Maintain expert-level working knowledge of Adobe GenStudio for enterprise content creation, brand asset management, and workflow automation; understand content moderation, version control, and rights management
• Advise on Firefly (generative imagery and design) and other generative AI capabilities within Experience Cloud; assess where AI-driven content generation reduces time-to-market and improves personalization at scale • Design architectures that integrate GenStudio outputs with Journey Optimizer, Experience Manager, and Real-Time CDP for AI-assisted content personalization and dynamic creative optimization
• Guide clients on managing generative AI in regulated industries; advise on model governance, content authenticity, disclosure requirements, and brand safety
• Stay current on new generative and predictive AI capabilities across Adobe’s roadmap and emerging third party AI tools; evaluate integration opportunities and competitive positioning
• Lead conversations with clients on AI maturity assessment: readiness for generative content, data quality for model training, team capability, and change management
Platform Expertise & Fluency
• Maintain expert-level working knowledge of Adobe Experience Cloud: Experience Platform (XDM, data lakes, activation), Real-Time CDP, Journey Optimizer (orchestration, AI-driven decisioning), Content Management, GenStudio, Firefly, Analytics, and audience segmentation
• Understand how AEC integrates with cloud data warehouses (Snowflake, Databricks, BigQuery), identity resolution solutions, customer data platforms, and third-party AI/ML platforms
• Stay current on Adobe product roadmaps, new capabilities (including AI feature releases), and release timelines; bring informed perspectives on how emerging generative and predictive AI addresses client challenges
• Translate vendor documentation, release notes, AI capability announcements, and best practices into actionable client guidance
• Maintain hands-on familiarity with AEC configuration, APIs, connectors, and AI features; stay fluent enough to evaluate feasibility and guide implementation approaches
Delivery Enablement & Technical Leadership
• Serve as the escalation point and technical authority for complex implementation challenges, including novel uses of generative AI; drive resolution of architectural, technical, or AI-readiness risks
• Partner with solution architects, engineers, and delivery leads to ensure designs are implemented as intended, quality standards are met, and AI-driven components deliver expected business outcomes
• Define and communicate non-functional requirements (performance, scalability, security, compliance, responsible AI governance) and acceptance criteria for technical work
• Conduct design reviews, code reviews (where appropriate), and architecture audits to ensure adherence to standards and best practices, including AI model governance and content authenticity controls
• Mentor solution architects, engineers, and other team members on architectural thinking, platform capabilities, responsible AI practices, and emerging patterns
Client Advisory & Thought Leadership
• Engage directly with client technology stakeholders and C-suite to frame technical strategy—including AI opportunity and risk—in business terms
• Bring outside-in perspective from the market, partner ecosystem, industry trends, and emerging AI capabilities into client conversations
• Lead business review discussions on technical health, capability expansion, AI readiness, and strategic roadmap alignment
• Develop and share client-facing technical narratives, architecture diagrams, and capability roadmaps that link to business outcomes, including AI-driven efficiency and personalization gains
• Educate clients on generative AI maturity levels: where their organizations stand, what investments are needed, and how to measure ROI on AI initiatives
• Contribute to internal and external thought leadership on Adobe, data architecture, generative AI application, responsible AI practices, and martech topics
Efficiency, Innovation & AI-Driven Practice
• Drive continuous improvement in engagement delivery through architectural patterns, reusable components, and automation—including AI-assisted tools for design, documentation, and client reporting
• Use AI tools as a core productivity multiplier: leverage GenAI for architecture documentation, proposal generation, client narrative development, and research synthesis
• Build and maintain a library of reference architectures, decision frameworks, playbooks, and AI use case patterns for common client scenarios • Evaluate emerging generative and predictive AI tools (both Adobe and third-party) that can accelerate solution design, implementation, or operational efficiency; pilot and share learnings with the team
• Collaborate with other Enterprise Architects to codify best practices, maintain architectural standards, and establish governance frameworks for responsible AI use across the practice
• 12+ years of experience in technology implementation, architecture, or consulting with at least 4+ years in a senior technical leadership or architecture role
• Deep, demonstrable expertise in modern data architecture and marketing technology stacks; working knowledge of cloud data warehouses (Snowflake, Databricks, BigQuery, Microsoft Fabric)
• Senior-level fluency in Adobe Experience Platform, Real-Time CDP, Journey Optimizer, or comparable customer experience / CDP platforms; able to lead capability and integration conversations without relying on a technical translator
• Working knowledge of generative AI and large language models (LLMs); practical experience evaluating or implementing generative AI tools; understanding of AI governance, bias mitigation, and responsible AI practices
• Proven track record designing and delivering large-scale, multi-platform integrations for enterprise clients
• Experience leading architecture and design activities in cross-functional delivery teams (architects, engineers, product, client technical teams)
• Strong communication skills: able to translate technical and AI complexity into executive-level narratives and work fluently with technical and non-technical stakeholders
• Excellent critical thinking, structured problem-solving, and ability to balance trade-offs across performance, cost, complexity, time-to-market, and responsible AI governance
• Familiarity with enterprise architectural frameworks and patterns (data mesh, domain-driven design, enterprise integration patterns, etc.)
• Active, hands-on engagement with AI tools as part of your technical practice: research synthesis, documentation, code generation, design, and responsible AI evaluation