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 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. Qualifications To be successful in this role, you will have - 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. - ServiceNow domain knowledge, including: Now Assist and Generative AI Skills / Skill Kit, AI Agents and Agentic workflows, AI Control Tower, Retrieval-Augmented Generation (RAG), Knowledge Graphs, Agent-to-Agent (A2A), and Model Context Protocol (MCP). - 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. Additional Information Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2025 Fortune Media IP Limited. All rights reserved. Used under license.

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 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. Qualifications To be successful in this role, you will have - 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. - ServiceNow domain knowledge, including: Now Assist and Generative AI Skills / Skill Kit, AI Agents and Agentic workflows, AI Control Tower, Retrieval-Augmented Generation (RAG), Knowledge Graphs, Agent-to-Agent (A2A), and Model Context Protocol (MCP). - 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. For positions in this location, we offer a base pay of $173,200- $270,600, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location. Additional Information Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2025 Fortune Media IP Limited. All rights reserved. Used under license.

• Translate business problems into scalable AI solutions. • Ensure responsible and measurable deployment of AI across the organization. • Help scale AI literacy and champion new tools and capabilities. • Guide end-to-end automation initiatives to improve productivity and decision quality. • Operate with high autonomy and work across diverse stakeholders to shape Yum!’s AI maturity. • Build and optimize enterprise AI initiatives. • Develop and execute AI literacy programs through the AI Academy. • Scale enterprise agents and integrate AI tools into daily workflows. • Build local communities of practice and train AI champions for AI adoption.

• Develop and execute a comprehensive enterprise data and AI strategy aligned with organizational priorities • Establish governance frameworks for data quality, stewardship, lifecycle management, and ethical AI use • Ensure compliance with regulatory standards (HIPAA, HITECH, CMS) • Lead the development, scaling, and adoption of AI/ML solutions across clinical, operational, and financial domains • Identify and prioritize high-impact use cases (e.g., predictive analytics, clinical decision support, automation) • Oversee model governance, validation, monitoring, and bias mitigation • Partner with clinical leaders to embed analytics into workflows and improve patient outcomes • Advance population health, risk stratification, and precision medicine initiatives • Deliver insights that improve operational efficiency, throughput, and cost performance • Collaborate with IT to design scalable, interoperable data platforms (cloud, data lakes, warehouses) • Ensure seamless integration across systems, including EHR platforms such as Epic • Enable real-time data access across care settings • Partner with academic and research organizations to advance clinical research and innovation • Support grant-funded initiatives, clinical trials, and translational research • Evaluate emerging technologies and strategic partnerships • Build and lead a high-performing data, analytics, and AI organization • Foster a culture of data literacy, innovation, and accountability • Educate executive leadership and the Board on data and AI strategy, capabilities, and risks • Establish enterprise data governance and privacy frameworks • Oversee cybersecurity alignment, risk management, and compliance • Manage budgets, capital planning, and ROI for data and AI investments • Lead vendor strategy, partnerships, and performance management