Solution Architect, ServiceNow
AI & Data
$173.2-270.6k
+ equity (when applicable) + variable/incentive compensation
Cloud-based digital workflows for enterprises
Be an early applicant
Cloud-based digital workflows for enterprises
1001+ employees
Be an early applicant
$173.2-270.6k
+ equity (when applicable) + variable/incentive compensation
1001+ employees
Company mission
To transform IT to revolutionize the enterprise.
Role
Who you are
- Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring 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
- 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
- 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. 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
What the job involves
- 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
- 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
- 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 regulatory requirements and internal policies
- Establish data governance frameworks that position metadata management, data stewardship, and knowledge graph capabilities as foundational trust layers for enterprise AI programs
- Guide customers in regulated industries on aligning data catalog and governance architectures to compliance and regulatory obligations, embedding controls into the design rather than as an afterthought
- 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 programmers, 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
Our take
ServiceNow provides cloud-based solutions that define, structure, manage, and automate services for enterprise operations, transforming old, manual ways of working into modern digital workflows. The company was founded in 2004 with a vision to build a cloud-based platform that would enable regular people to route work effectively through the enterprise.
Much as Salesforce enables a company to manage its external clients by keeping a record of all contacts and interactions, ServiceNow promises an internal system to meet the needs of employees. It has succeeded in claiming half the market, setting itself apart from legacy IT service-management software players like BMC Software, Hewlett Packard Enterprise, Cherwell Software and CA Technologies.
The company's success comes from two product traits: simplicity and customisability. ServiceNow's IT tools don't require the IT department to set them up. Once running, they offer a single collection centre for requests, data points and checklists, all of which can in turn be analysed by algorithms to predict needs, flag concerns and measure efficiency.
The company has more than 7,700 customers, including 85% of the Fortune 500 list of the United States' largest corporations. ServiceNow now looks to increase its revenue threefold in the upcoming years and has entered into a 5-year partnership plan with Visa, beginning with the launch of a Visa-integrated dispute resolution solution for issuers. The company is prioritising organic growth over mergers and acquisitions, with a target revenue of $15B, something which its Visa partnership will no doubt aid in achieving.
Freddie
Company Specialist at Welcome to the Jungle
Insights
16% employee growth in 12 months
Company
Funding (last 2 of 6 rounds)
Mar 2012
$11m
GROWTH EQUITY VC
Feb 2012
$17.9m
GROWTH EQUITY VC
Total funding: $83.8m
Company benefits
- Generous family leave
- Matched donations
- Annual learning stipends
- Flexible PTO
- Competitive retirement plan
- Paid volunteer time
Company HQ
Santa Clara, CA
Salary benchmarks
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