• Become an expert on Loop’s platform, ecosystem, and integrations, including the carrier, 3PL, OMS, WMS, and tax/compliance partners most common in EMEA and APAC, staying up to date on the latest builds. • Provide technical support to our Sales, Post Sales, and Partner teams through Slack, in-person and virtual meetings, with availability that works across UK, European, and APAC time zones when needed. • Vet and close deals from a technical requirements perspective, collaborating with Sales, development partners, and agencies operating in EMEA and APAC markets. • Create customised product demos and proofs-of-concept, including front-end configurations and region-specific scenarios such as cross-border returns, multi-currency, VAT/IOSS handling, and localised carrier flows, and present these solutions to internal and external audiences. • Become an SME on our APIs, webhooks, integrations, and front-end customizations for both internal and external partners, including merchants running headless, composable, or non-Shopify-native architectures. • Partner closely with merchants and agencies to scope and recommend solutions, including customizations to the shopper-facing return experience and the back-end logistics flows that sit behind it (3PL handoffs, warehouse receiving, label generation, reverse logistics protocols). • Help enable our Sales teams on the technical aspects of Loop, ensuring they’re confident in articulating product capabilities to merchants in market. • See and improve the whole system: solve new problems, evaluate workarounds, collaborate with Engineering, Product, and Design, and explore creative ways to develop on the Loop platform.

Role Description 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 operationalizing 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 programs, 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 - Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. - 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. - 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. - 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. - 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. 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.

• Partner with account executives throughout the sales cycle as the primary presales resource, providing deep product expertise and solution guidance. • Conduct technical discovery sessions to understand client requirements, integration needs, and business objectives. • Design and present tailored product demonstrations and tailored solutions that address specific client pain points and use cases. • Respond to technical questions and objections, articulating complex concepts in clear, business-relevant language to both technical and non-technical audiences. • Develop solution architectures, data mapping, and integration plans with third-party platforms (e.g., Salesforce, HubSpot, Stripe, PayPal, Zapier). • Support RFP/RFI responses, ensuring technical accuracy and compliance with standards such as PCI and GDPR. • Gather and relay client feedback to Solution Architecture and Product teams, contributing to product enhancements and roadmap decisions. • Stay current on fundraising technology trends, industry best practices, and competitor offerings. • Provide technical enablement and training to the Sales team, sharing insights and best practices. • Foster strong relationships with prospects and customers, ensuring technical satisfaction throughout the sales process. • At Fundraise Up, AI is a default tool, not an experimental one. We expect every team member to actively use AI in their day-to-day work, identify where AI can change the shape of problems in their function, and grow their fluency as the tools evolve. You should already be using AI meaningfully in your work and understand where it adds value and how it can improve the way you operate.

• Designs, develops, and oversees the implementation of software solutions, ensuring that the new solutions align with the existing enterprise architecture from technical, business, user, and other perspectives. • Translate business requirements into well-architected solutions and review detailed designs in collaboration with the Business Systems teams to implement end-to-end integrated systems. • Collaborate with key stakeholders to understand and accurately define complex problems, setting engagement objectives and scope. • Develop work plans and coordinate activities across multiple project workstreams, ensuring comprehensive solutions are created. • Assess technical needs and capabilities during implementation, using an analytical approach to understand all related technologies and topics. • Evaluate new technologies and vendors in support of systems development efforts and recommend technologies that will increase effectiveness and systems flexibility. • Ensure fit for purpose by conducting vendor evaluations, proofs-of-concept, and MVP definition. • Regular communication with IT specialists and enterprise architects to develop and implement complex technology and business solutions that fits the enterprise architecture. • Create a comprehensive architecture for application and software solutions, ensuring they fit into the existing enterprise architecture. • Guide the organization to incorporate architecture design patterns, system best practices and standards in architecture, software, security, privacy, data cleanliness, and infrastructure. • Cooperate with all development teams, understanding how every product and service works within the solution and enterprise architecture. • Oversee the successful delivery of quality end solutions to end users. • Analyze the business impact of technical choices on the client’s business processes, providing strategic direction on the solution. • Supervise and guide development teams ensuring the solution developed aligns to the solution design and fits with enterprise architecture. • Continuously research emerging technologies, proposing changes to the existing enterprise and solution architecture to improve overall efficiency and effectiveness.