Ai Transformation Architect Expert Services

## About the role As part of the Expert Services AI Practice, the AI Transformation Architect will serve as a senior strategic and technical lead, reshaping how enterprise organizations adopt AI at the core of their operating models. This role goes beyond implementation — it bridges C-suite advisory, enterprise architecture, and organizational change to deliver lasting transformation outcomes. The AI Transformation Architect will operate at the intersection of AI strategy, solution architecture, and customer success — leading engagements from transformation vision and use-case definition through architecture design, governance, adoption, and ongoing value realization. ## What you will do in this role ### AI Strategy & Transformation Advisory - Lead enterprise AI transformation engagements — from opportunity identification and business case development through to operating model design and value realization. - Advise C-suite and senior stakeholders on AI strategy, prioritization frameworks, and transformation roadmaps tailored to their industry, maturity, and risk appetite. - Facilitate discovery workshops, current-state assessments, and future-state visioning sessions to establish a shared transformation agenda. - Define AI-enabled target operating models, including process redesign, workforce impact analysis, and governance structures. ### Solution Architecture & Delivery Leadership - Design end-to-end solution architectures spanning Now Assist, AI Agents, Agentic workflows, AI Control Tower, RAG, knowledge graphs, and enterprise integrations (A2A, MCP). - Lead scoping and solutioning for complex, multi-workload AI engagements — ensuring architectural integrity, scalability, and alignment to customer outcomes. - Provide hands-on architecture leadership during pilot and early-phase delivery, establishing patterns and standards for broader team execution. - Develop reusable practice IP: reference architectures, deployment patterns, transformation playbooks, and verticalized use-case catalogs. ### AI Governance, Risk & Responsible AI - Define and embed AI governance frameworks covering data stewardship, model risk, bias controls, audit trails, and compliance postures. - Support customers in operationalizing responsible AI practices aligned to regulatory requirements and internal policies. - Partner with AI Control Tower to establish monitoring, observability, and continuous optimization capabilities post-deployment. ### Adoption, Enablement & Change Management - Lead AI adoption strategies including readiness assessments, stakeholder engagement plans, AI literacy programs, and change communications. - Define adoption KPIs and value realization metrics; track and report outcomes; provide consultative guidance for continuous optimization and expansion. - Coach customer teams to build internal AI capability, reducing dependency and accelerating long-term self-sufficiency. - Monitor adoption, usage, and value realization metrics post-deployment; provide recommendations for risk mitigation and growth. ### Practice Development & Thought Leadership - Collaborate cross-functionally with Sales, Solution Consulting, Customer Success, Platform, and Product teams to embed AI advisory across the customer lifecycle. - Build and maintain industry-specific AI advisory playbooks and frameworks — verticalized use-case catalogs, value models, governance templates, and deployment patterns — to support scalable, repeatable delivery. - Act as a thought-leader internally and externally: contribute to white papers, points-of-view, reference architectures, best-practice guides, and represent the organization at AI forums and customer briefings. - Support pre-sales by qualifying opportunities, shaping proposals, and presenting transformation vision to executive buyers. ## Qualifications - Experience leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving — including AI-powered tools, workflow automation, AI-driven insights, or AI's potential impact on the function or industry. - 10+ years of experience in management consulting, enterprise architecture, or a senior technology advisory role, with a demonstrated focus on Artificial Intelligence, Machine Learning, or digital transformation at enterprise scale. - ServiceNow domain knowledge, including: Now Assist and Generative AI Skills / Skill Kit, AI Agents and Agentic workflows, AI Control Tower, Retrieval-Augmented Generation (RAG), Knowledge Graphs, Agent-to-Agent (A2A), and Model Context Protocol (MCP). - Proven track record designing and managing complex, multi-stakeholder AI or digital-transformation engagements — including use-case definition, business case development, integration, data strategy, governance, and operational adoption. - Strong understanding of enterprise data architecture, data quality, knowledge management, integrations, and compliance and regulatory frameworks. - Excellent communication and interpersonal skills — ability to articulate technical and business value to C-level executives, align stakeholders, and influence strategic decision-making. - Experience working in fast-paced, dynamic environments with capability to manage ambiguity and tailor consulting deliverables to different customer maturity levels, from early adopters to AI-ready enterprises. - Broad familiarity with the ServiceNow platform and modules (ITSM, CSM, FSM, HRSD, App Engine), ideally including implementation or architecture experience. ServiceNow certifications (Certified System Administrator, Certified Implementation Specialist, Certified Technical Architect) are desirable. - AI/ML certifications (e.g. AWS Machine Learning Specialty, Google Professional Machine Learning Engineer, or equivalent) are desirable. - Background in one or more target industries — Financial Services, Healthcare, Public Sector, Manufacturing, or Retail.