• Lead discovery workshops to understand client objectives, existing systems, data flows, and constraints. • Define target-state architecture for CRM, CDP, and marketing automation, including integration patterns, governance, and scalability considerations. • Translate business problems into technical solution options, with clear trade-offs, effort estimates, and risks. • Guide implementations end-to-end, from documentation and planning through detailed requirements and support for build. • Produce high-quality technical artifacts including architecture diagrams, data flow maps, event and identity models, and implementation roadmaps. • Write clear technical requirements for engineers, partnering with technical project management to scope, sequence, and deliver work. • Partner with client stakeholders to drive decisions and keep delivery aligned to outcomes, timelines, and dependencies. • Architect and support integrations across the MarTech stack, including CDPs, marketing automation platforms, analytics, attribution, and enrichment tools. • Design data schemas and event tracking plans that support lifecycle use cases and analytics needs. • Support ETL and reverse ETL patterns to activate data into downstream destinations. • Ensure solutions account for omnichannel transactional and marketing messaging, customer journeys, user states, and event-driven automation.

• Own configuration, administration, and ongoing maintenance of our AI-powered application platform • Collaborate with infrastructure engineers to shape the framework and standards that govern how AI-assisted applications are built, reviewed, and deployed. • Design and build tooling that enables teams to develop and iterate on applications with greater independence and less engineering overhead • Evaluate AI-generated code for security, scalability, and production readiness, and define code review standards specific to AI-assisted development workflows • Serve as a technical advisor to non-technical stakeholders — helping them understand what is possible, where risk lives, and when engineering involvement is required • Establish and promote best practices for AI-assisted development across the engineering organization • Partner with the AI Solutions team and engineering leadership to define the long-term architecture of this platform as it scales

• Lead the design and architecture of customer’s Agiloft instance, ensuring solutions are clean, effective, scalable, maintainable, and meet the complexity of enterprise-level needs. • Capture, analyze, and document client requirements. • Develop comprehensive design documents and implementation plans for team collaboration and execution. • Provide mentorship and constructive feedback to junior team members, ensuring high-quality deliverables. • Manage client interactions, addressing escalations with a solutions-focused mindset. • Deliver thorough documentation and client training to ensure successful solution adoption. • Offer feedback to product and engineering teams to drive continuous product improvement. • Support and advise system integration (SI) partners to enhance overall implementation outcomes. • Contribute to internal initiatives aimed at improving implementation processes and client success. • Maintain current, deep knowledge of Agiloft product offerings, roadmap, and best practices. • Apply product knowledge effectively in delivering high-quality consulting services • Proactively learn and adopt new features, including AI-enabled capabilities, and translate them into customer value. • Actively and responsibly use AI to improve efficiency, productivity, and value delivery, continuously evaluating where AI can enhance processes, workflows, and outcomes. • Approximately 10% travel required. • Other duties as assigned

• Own technical demos for enterprise prospects alongside AEs — running them daily at high volume • Be the go-to technical expert on every customer call: architecture questions, integration scoping, platform positioning • Manage ~50 active opportunities at once across a fast, no-nonsense sales cycle • Help customers get live — supporting post-sales onboarding on AI Gateway architecture for production (primarily pre-sales focused) • Feed customer insights directly back to the product and engineering teams — your voice shapes the roadmap