About the job
As part of the Expert Services AI Practice, the Solution Architect - AI & Data 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.
Responsibilities
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.
Design end-to-end solution architectures spanning Now Assist, AI Agents, Agentic workflows, AI Control Tower, RAG, knowledge graphs, and enterprise integrations (A2A, MCP).
Qualifications
Minimum
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.
Experience facilitating executive AI strategy engagements — including visioning workshops, maturity assessments, and transformation roadmap sessions — where the output is a customer-owned AI narrative, not just a delivery plan.
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.
Demonstrated ability to architect enterprise data catalog and metadata management strategies, with knowledge of platforms.
Excellent communication and interpersonal skills — ability to articulate technical and business value to C-level executives, align stakeholders, and influence strategic decision-making.
AI domain knowledge required, including: Generative AI Skills, AI Agents and Agentic workflows, Retrieval-Augmented Generation (RAG), Knowledge Graphs, Agent-to-Agent (A2A), and Model Context Protocol (MCP).
Working knowledge of knowledge graph principles, semantic technologies, and standards (RDF, SPARQL) as applied to enterprise data architecture.
Broad familiarity with the ServiceNow platform and modules (ITSM, CSM, FSM, HRSD, App Engine), ideally including implementation or architecture experience.
Preferred
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 — is highly desirable.