• Participate in active client AI projects as the hands-on AI specialist • Design and build AI agent workflows, prompt chains, and orchestration logic • Develop and refine prompts for specific business use cases (prompt engineering) • Analyze existing client workflows and identify opportunities for AI enhancement • Create working prototypes and proofs-of-concept to validate approaches • Collaborate with developers on implementation handoff and technical specifications • Support presales engagements with AI solution proposals and feasibility assessments • Conduct business domain analysis to identify where AI creates genuine value • Translate client business problems into AI-addressable solutions • Prepare demonstrations and prototype artifacts for client presentations • Provide input on effort estimation for AI components of proposals • Monitor AI news, model releases, tool updates, and emerging techniques • Evaluate new AI platforms, frameworks, and services for potential adoption • Experiment with new approaches and share findings • Document patterns, techniques, and lessons learned from project work • Contribute to internal knowledge bases and training materials • Design agentic workflows using orchestration frameworks (e.g., n8n, LangGraph, custom pipelines) • Optimize existing business workflows by introducing AI capabilities • Define conversation flows, tool usage patterns, and handoff logic for AI agents • Specify context management, memory strategies, and retrieval patterns

• Manage a caseload of learners, building trusted relationships through structured one‑to‑one coaching and group workshops • Support learners at different stages of confidence and digital maturity, adapting your approach to meet individual needs • Create an inclusive, psychologically safe learning environment where learners feel comfortable asking questions, practising new skills, and learning from mistakes • Encourage learners to take ownership of their development, building confidence through practical application and reflection • Coach learners to use Microsoft 365 tools to improve everyday productivity • Guide learners in the practical use of Microsoft Copilot and other AI tools • Support learners to develop safe, ethical, and responsible AI habits • Help learners recognise opportunities to apply AI enabled workflows in real workplace tasks • Support learners to develop foundational digital support skills, such as diagnosing simple application issues, providing user support, and troubleshooting • Progress, Quality & Outcomes: Guide learners through programme milestones, assessments, and portfolio evidence • Collaborate with colleagues across Operations, Product, and Curriculum to deliver a consistent and high-quality learner experience

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. - 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. - 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). - 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.

Role Description - Design and develop enterprise-grade Generative AI and Agentic AI solutions. - Build AI-powered assistants, copilots, and intelligent workflow automation platforms. - Implement and optimize: - Large Language Models (LLMs) - Retrieval Augmented Generation (RAG) - Multi-Agent Systems - Semantic Search architectures - Develop AI orchestration frameworks for autonomous and collaborative AI agents. - Build scalable AI pipelines and microservices using Python and modern AI frameworks. - Design vector search and enterprise knowledge retrieval solutions. - Fine-tune prompts, optimize inference performance, and improve AI response quality. - Develop secure API integrations and event-driven AI architectures. - Collaborate with product, architecture, security, and engineering teams. - Ensure responsible AI governance, security, compliance, and observability standards. - Support deployment, monitoring, and continuous improvement of AI systems in production. Company Description At Zensar, we’re “experience-led everything”. We are committed to conceptualizing, designing, engineering, marketing, and managing digital solutions and experiences for over 130 leading enterprises. We are a company driven by a bold purpose: Together, we shape experiences for better futures. Whether for our clients, our people, or the world around us, this belief powers everything we do. At the heart of our culture is ONE with Client - a set of four core values that reflect who we are and how we work: One Zensar, Nurturing, Empowering, and Client Focus. Part of the $4.8 billion RPG Group, we’re a community of 10,000+ innovators across 30+ global locations, including Milpitas, Seattle, Princeton, Cape Town, London, Zurich, Singapore, and Mexico City. Explore Life at Zensar and join us to Grow. Own. Achieve. Learn. to be the best version of yourself. We believe the best work happens when individuality is celebrated, growth is encouraged, and well-being is prioritized. We are an equal employment opportunity (EEO) and affirmative action employer, committed to creating an inclusive workplace. All qualified applicants will be considered without regard to race, creed, color, ancestry, religion, sex, national origin, citizenship, age, sexual orientation, gender identity, disability, marital status, family medical leave status, or protected veteran status.