Solution Architect - AI & Data
$173,200–$270,600 year
RemoteUnited States or San Diego, California, United States
Job Summary
Lead enterprise AI transformation engagements from opportunity identification through operating model design and value realization. Advise C-suite stakeholders on strategy, prioritization frameworks, and roadmaps tailored to industry maturity and risk appetite. Facilitate discovery workshops, current-state assessments, and future-state visioning sessions to establish shared transformation agendas. Design end-to-end solution architectures spanning Now Assist, AI Agents, Agentic workflows, RAG, knowledge graphs, and enterprise integrations. Lead architectural design of enterprise data catalog programs, defining scope, platform selection, and phased adoption roadmaps. Define and embed AI governance frameworks covering data stewardship, model risk, bias controls, and compliance postures. Coach customer teams to build internal AI capability while monitoring adoption metrics and providing continuous optimization guidance. Collaborate cross-functionally with Sales, Solution Consulting, and Customer Success teams to embed AI advisory across the customer lifecycle.
Required Qualifications
- Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving
- 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
- 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
- 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)
- ServiceNow certifications (Certified System Administrator, Certified Implementation Specialist, Certified Technical Architect)
Desired Qualifications
- AI/ML certifications (e.g. AWS Machine Learning Specialty, Google Professional Machine Learning Engineer, or equivalent)
- Background in one or more target industries — Financial Services, Healthcare, Public Sector, Manufacturing, or Retail
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