Solution Architect - AI & Data

Company Description

It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today — ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone.

Job Description

The Team

The Customer Excellence Group at ServiceNow works with customers to help them achieve their business outcomes by providing prescriptive guidance. As part of the Customer Excellence Group, you will work with our customers to drive consumption, adoption, and customer satisfaction and ultimately help our customers grow their business on the ServiceNow platform by getting them to see the value of their ServiceNow investment.

Solution Architect - AI & Data, Expert Services

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.

The Solution Architect - AI & Data 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.
• Architect enterprise data catalog strategies using platforms defining target-state designs that align metadata management, data lineage, and governance structures to broader AI and business objectives.
• Define integration patterns and architectural standards for connecting data catalog solutions across heterogeneous enterprise environments — cloud platforms, data warehouses, BI layers, and ServiceNow workflows.

Data Architecture & Catalog Strategy

• Lead the architectural design of enterprise data catalog programs — defining scope, platform selection criteria, governance operating models, and phased adoption roadmaps.
• Advise on the strategic application of knowledge graph concepts, semantic technologies, and ontological frameworks (RDF, SPARQL) to enterprise data and AI use cases.
• Shape data architecture principles and standards that underpin AI readiness — including data lineage, metadata quality, classification taxonomies, and access governance.
• Translate complex data architecture requirements into clear, actionable designs that can be executed by delivery and technical teams.
• Define success metrics and maturity benchmarks for data catalog programs, enabling customers to track progress and demonstrate value to executive stakeholders.

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 operationalize responsible AI practices aligned to regulato