Solution Architect - AI & Data

Salary: $173,200 - 270,600 per year Requirements:

• We expect at least 10 years of experience in management consulting, enterprise architecture, or senior technology advisory roles, with a strong focus on artificial intelligence, machine learning, or enterprise-scale digital transformation.
• We look for experience leading executive-level AI strategy sessions, including vision workshops, maturity assessments, and roadmap development that result in a customer-owned transformation narrative.
• We require a proven history of managing complex, multi-stakeholder AI or digital transformation programs spanning use-case definition, business case creation, integration, data strategy, governance, and adoption.
• We value a solid grasp of enterprise data architecture, data quality, knowledge management, integrations, and compliance or regulatory frameworks.
• We need demonstrated ability to design enterprise data catalog and metadata management strategies, including familiarity with relevant platforms.
• We expect excellent communication and interpersonal skills, with the ability to explain technical and business value to senior executives, align stakeholders, and shape strategic decisions.
• We look for the ability to work effectively in fast-moving, dynamic environments while handling ambiguity and adapting consulting deliverables to different customer maturity levels.
• We prefer working knowledge of knowledge graph concepts, semantic technologies, and standards such as RDF and SPARQL as applied to enterprise data architecture.
• We value broad familiarity with the ServiceNow platform and modules such as ITSM, CSM, FSM, HRSD, and App Engine; implementation or architecture experience is ideal.
• ServiceNow certifications such as Certified System Administrator, Certified Implementation Specialist, or Certified Technical Architect are desirable.
• AI/ML certifications such as AWS Machine Learning Specialty, Google Professional Machine Learning Engineer, or an equivalent credential are desirable.
• Experience in industries such as Financial Services, Healthcare, Public Sector, Manufacturing, or Retail is highly desirable.

• We lead enterprise AI transformation engagements from opportunity discovery and business case development through operating model design and value realization.
• We advise C-suite leaders and senior stakeholders on AI strategy, prioritization, and transformation roadmaps tailored to their industry, maturity, and risk profile.
• We facilitate discovery workshops, current-state assessments, and future-state vision sessions to align stakeholders around a shared transformation agenda.
• We define AI-enabled target operating models, including process redesign, workforce impact analysis, and governance structures.
• We design end-to-end solution architectures covering Now Assist, AI Agents, agentic workflows, AI Control Tower, RAG, knowledge graphs, and enterprise integrations such as A2A and MCP.
• We lead scoping and solution design for complex, multi-workload AI engagements, ensuring architectural soundness, scalability, and alignment to customer outcomes.
• We provide hands-on architecture leadership during pilots and early delivery phases, establishing reusable patterns and standards for broader execution.
• We create reusable practice assets such as reference architectures, deployment patterns, transformation playbooks, and verticalized use-case catalogs.
• We architect enterprise data catalog strategies, defining target-state designs that align metadata management, data lineage, and governance with AI and business objectives.
• We define integration patterns and architectural standards for connecting data catalog solutions across cloud platforms, data warehouses, BI layers, and ServiceNow workflows.
• We lead the architectural design of enterprise data catalog programs, including scope definition, platform selection criteria, governance operating models, and phased adoption roadmaps.
• We advise on knowledge graph concepts, semantic technologies, and ontological frameworks such as RDF and SPARQL for enterprise data and AI use cases.
• We shape data architecture principles and standards that support AI readiness, including lineage, metadata quality, classification taxonomies, and access governance.
• We translate complex data architecture requirements into practical designs that delivery and technical teams can execute.
• We define success measures and maturity benchmarks for data catalog programs so customers can track progress and demonstrate value to executives.
• We establish AI governance frameworks covering data stewardship, model risk, bias controls, audit trails, and compliance postures.
• We help customers operationalize responsible AI practices aligned with regulatory requirements and internal policies.
• We build data governance frameworks that position metadata management, stewardship, and knowledge graph capabilities as core trust layers for enterprise AI programs.
• We guide customers in regulated industries on aligning governance and data catalog architectures with compliance obligations.
• We partner with AI Control Tower to establish monitoring, observability, and continuous optimization after deployment.
• We lead AI adoption strategies, including readiness assessments, stakeholder engagement plans, AI literacy programs, and change communications.
• We define adoption KPIs and value-realization metrics, track results, and provide recommendations for continuous optimization and expansion.
• We coach customer teams to build internal AI capability and reduce long-term dependency.
• We monitor post-deployment adoption, usage, and value outcomes, and recommend actions to mitigate risk and unlock growth.
• We collaborate with Sales, Solution Consulting, Customer Success, Platform, and Product teams to embed AI advisory across the customer lifecycle.
• We develop industry-specific AI advisory playbooks and frameworks to enable scalable, repeatable delivery.
• We act as internal and external thought leaders through white papers, points of view, reference architectures, best-practice guides, and customer or forum briefings.
• We support pre-sales by qualifying opportunities, shaping proposals, and presenting the transformation vision to executive buyers.

• AI
• AI Agents
• AWS
• Architect
• Cloud
• Support
• ITSM
• Machine Learning
• MCP
• RAG
• RDF
• ServiceNow

More:

We are ServiceNow, a global market leader founded in San Diego in 2004, building an intelligent cloud platform that connects people, systems, and processes so organizations can work smarter, faster, and better. Our AI-enhanced technology supports more than 8,100 customers, including 85% of the Fortune 500, and we are focused on helping make the world work better for everyone. This role sits within our Customer Excellence Group and Expert Services AI Practice, where we partner closely with customers to drive consumption, adoption, satisfaction, and measurable business value on the ServiceNow platform. We offer flexible work personas across a distributed environment, competitive compensation with base pay, equity where applicable, variable incentive opportunities, and a benefits package that includes health plans, 401(k) matching, ESPP, matching donations, flexible time away, and family leave programs. We also foster an inclusive, accessible, and equal opportunity workplace.

last updated 33 week of 2026