Enterprise Architect

dentsu•Time, IL

2d•$113,000 - $132,500•Remote

About The Position

The Enterprise Architect is CDS's technical strategy leader for Adobe Experience Cloud implementations across the data, content, and customer journey domains. This role is the authoritative voice on architectural decisions, platform integration, technical feasibility, and scalability—ensuring that solutions are designed for enterprise performance, reliability, and growth. In an increasingly AI-driven landscape, Enterprise Architects lead the integration of generative AI and predictive capabilities across the Adobe ecosystem, advising clients on how AI accelerates content creation, personalization, decisioning, and operational efficiency. Enterprise Architects own the end-to-end technical vision for complex, multi-platform implementations. They translate business requirements and technical constraints into robust, scalable architectures that leverage Adobe's ecosystem (Experience Platform, Real-Time CDP, Journey Optimizer, Content Management, GenStudio, Firefly) alongside complementary data and marketing technology stacks. This role partners closely with Engagement Leads to deliver strategic advisory and technical confidence in all engagements, with growing emphasis on AI and generative capabilities as table-stakes in modern customer experience platforms. Enterprise Architects are proactive technologists who combine deep platform expertise with business acumen and forward-looking AI fluency. They are conversant in modern data architecture, identity resolution, personalization engines, marketing technology orchestration, and generative AI applications (content creation, AI-driven decisioning, predictive analytics). They use architectural frameworks and patterns to reduce complexity, mitigate risk, and accelerate time-to-value while managing responsible AI practices. They mentor and empower solution architects and technical teams, and they stay current on emerging capabilities and best practices across the Adobe ecosystem and adjacent platforms.

Requirements

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

Nice To Haves

Adobe Certified Professional or Advanced certification (Experience Platform, Real-Time CDP, Journey Optimizer, Analytics, GenStudio)
Hands-on experience with Adobe GenStudio, Firefly, or other Adobe AI/generative capabilities
Active participation in Adobe Champion, Developer Community, or partner ecosystem programs with focus on AI/generative capabilities
Certifications in cloud data warehouse platforms (SnowPro, Databricks Lakehouse Fundamentals, Google Cloud Architect, etc.)
Experience architecting AI applications: model governance, responsible AI frameworks, bias detection and mitigation, explainability
Experience architecting identity resolution and data governance frameworks
Published thought leadership on generative AI, responsible AI practices, or AI in marketing/customer experience contexts
Speaking engagements at industry conferences on data architecture, AI application, or martech topics
Experience in a consultancy, systems integrator, or enterprise software services firm
Background or certification in enterprise solution architecture (ITIL, Togaf, or similar frameworks)
Track record mentoring junior architects or leading architectural communities of practice
Experience with agile and modern delivery methodologies in complex, multi-vendor environments
Advanced degree (Master's) in Computer Science, Data Science, AI/ML, Business Administration, or related field

Responsibilities

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
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
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
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
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
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