Customer Experience AI Architect

Role Overview

• Learn and deeply understand CX priorities, processes, systems, stakeholders, and pain points across Professional Services, Customer Adoption Management, Managed Services, and Customer Enablement; with a focus on delivery/implementation.
• Identify and translate AI use cases that improve productivity, customer experience, time-to-value, and employee effectiveness across the post-sales customer journey.
• Maintain and prioritize a CX AI opportunity backlog based on value, feasibility, risk, and strategic alignment — managing both inbound requests from CX leaders and proactively identified opportunities.
• Design and build production-grade AI tools and workflows, including AI-assisted implementation workflows, AI copilots for consultants, and automated customer communications.
• Build and maintain reliable integrations, automations, and data sync patterns across the CX stack, improving data quality, reducing tool sprawl, and ensuring actions are triggered from trusted signals.
• Establish an AI/automation operating cadence for CX: intake → prioritization → build → QA → release → measure → iterate, with clear owners, SLAs, and documentation to reduce ad hoc requests and rework.
• Act as the connector between CX and IT, communicating needs, priorities, and delivery context to ensure AI solutions are governed, supportable, and scalable.
• Act as the connector between CX and Product & Technology, influencing architecture, integrations, and onboarding of Vena AI solutions and representing CX/PS in the product team’s AI vision.
• Partner with IT, Security, Data, and Governance teams to ensure all AI solutions meet Vena’s responsible AI standards and actively contribute to evolving the governance framework as CX AI matures.
• Drive adoption through enablement: stakeholder training, playbooks, change management, and feedback loops that turn prototypes into repeatable, scalable workflows used day-to-day.
• Possible travel to Vena headquarters in Toronto and or customer offices in the US

Requirements

• 5+ years in Professional Services, Solution Architecture, Customer Experience, or similar role, with a track record of delivering AI tools in production enterprise environments.
• Hands-on experience building and deploying AI applications for enterprise, including LLM/GenAI development, prompt engineering, RAG architectures, and AI agent frameworks (Claude, OpenAI, Copilot Studio, or equivalent).
• Ability to understand CX business processes and translate pain points into clear AI use cases, requirements, value hypotheses, and success measures.
• Experience working in Professional Services or similar technical customer-facing roles, with strong intuition for where AI eliminates friction in implementation and adoption, driving better customer outcomes and stronger realized value.
• Ability to prioritize AI opportunities using value, feasibility, risk, urgency, and strategic alignment, and to influence without authority across teams they don’t own.
• Comfort with API integrations, workflow automation tools, and working with data and BI platforms (e.g., Snowflake, Power BI) to measure and communicate AI impact.
• Good judgment around data sensitivity, privacy, security, accuracy, user experience, and responsible AI usage.
• Resilience and comfort operating in ambiguity. This is a transformational role in a fast-moving space that rewards curiosity, bias for action, and a growth mindset.
• Interest in AI and willingness to explore AI-driven solutions to enhance performance and drive efficiencies.