Company Description It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started. Join us to put AI to work for people. Job Description About the Role As a AI Agent Engineer (AIAE), specializing in strategic implementations and partnership initiatives at Moveworks, you’ll be responsible for ensuring a successful technical delivery of the Moveworks platform for new customers and initiatives, working alongside Implementation Managers and the broader Partner ecosystem to understand customer requirements, perform discovery, and drive all technical aspects around our post-sales engagements. You are a critical, high-leverage technical individual that operates at the intersection of Customer Success, Product Management, and Engineering. Your primary mission is to translate complex customer business process challenges into innovative, high-impact AI solutions built on our platform. This role provides full-stack ownership of technical success, allowing you to not only deploy capabilities in the current product but also directly influence the product's evolution by ensuring that learnings are folded back into our core platform. This is not a back-office engineering role. You will be in front of customers regularly and are expected to travel up to 25% of the time. Core Responsibilities & Impact - Customer Technical Relationships: Partner deeply with customers throughout the entire delivery lifecycle of AI Agents on the Moveworks Platform: Vision-Lock, Solution Design/Architecture, Building, Tuning, and launch. - Custom Solution Design: Architect, design and consult with customers to develop high-impact technical AI solutions on the Moveworks platform by helping them leverage AI in novel and meaningful ways to solve complex business challenges. - Integration & Implementation: Design and build secure, performant integrations between the Moveworks Platform and customer enterprise systems including ServiceNow, Workday, Okta, Jira, and others. - Strategic Advisory: Serve as a trusted technical advisor, helping customers develop their Agentic AI roadmap and upskilling their teams to operate the platform independently over time. - Product Feedback Loop: Synthesize on-the-ground customer feedback and technical gaps, working directly with Moveworks Engineering and Product teams to influence platform evolution. - Reusability & Knowledge Sharing: Generalize successful customer solutions into reusable templates and share learnings broadly across the team. About You You are a technical generalist who genuinely enjoys working directly with customers. You thrive at the intersection of engineering, consulting, and customer success — and you're equally energized by solving a complex integration problem and presenting a solution narrative to a customer's executive team. - Customer-First Mindset: You have strong communication and relationship skills, and you're compelled to develop and deliver compelling solution narratives through high-quality artifacts — architecture diagrams, solution proposals, SOWs — tailored to both technical and business audiences. - Technical Mastery: You have a strong grasp of API-based systems integration, LLM-based systems design including prompt engineering, context engineering, and data modeling. - Curiosity & Adaptability: You are a rapid learner with high technical aptitude — equally curious about what's happening under the hood and why a business process works the way it does. - Product Judgment: You have strong product taste and are obsessed with delivering exceptional experiences for end users. - Entrepreneurial Grit: You lean into ambiguity, navigate legacy systems with patience, and actively seek exposure across engineering, product, and business functions. - Accountability: You have a strong sense of personal accountability to both customers and internal teammates who rely on your expertise. Qualifications Required: - 8+ years of experience in a customer-facing technical role — Solutions Engineer, Customer Success Engineer, Solutions Architect, Implementation Consultant, or Consulting Engineer - Demonstrated track record of driving successful technical adoption with mid-to-large enterprise customers - Experience designing, building, and launching full-stack workflows and automations leveraging REST APIs, iPaaS tools (Workato, Azure Functions, AWS Lambdas, ServiceNow Flow Designer), or scripting languages (Python, JavaScript, Golang) - Proven ability to determine methods and procedures on new assignments independently, exercising strong judgment to select the right approaches and drive results across complex, cross-functional problems - Experience leading projects and coordinating other team members, with strong networks across departments and key external stakeholders - Willingness and ability to travel up to 25% of the time - Ability to operate across multiple business functions and technical domains Preferred: - Familiarity with enterprise platforms such as ServiceNow, Jira Service Desk, Zendesk, Workday, or Okta - Familiarity with Linux and Windows environments and command line - Current on the latest AI tools, frameworks, and agentic design patterns — and thoughtful about how to apply them to build reliable, scalable solutions FD21 For positions in this location, we offer a base pay of $137,700 - $241,000, 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. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.

• Design, develop, and deploy AI-powered applications using Large Language Models. • Design and implement Agentic AI solutions capable of executing multi-step reasoning and autonomous workflows. • Develop and maintain AI agents and agent orchestration workflows that coordinate multiple tasks, services, and external systems. • Integrate AI capabilities with enterprise applications, APIs, and external services. • Collaborate with product owners and business stakeholders to translate business requirements into scalable AI solutions. • Apply Spec-Driven Development practices to improve solution quality, traceability, and implementation consistency. • Leverage AI-driven software development lifecycle practices to accelerate development, testing, documentation, and delivery. • Evaluate, test, and optimize AI models to improve response quality, reliability, and overall performance. • Participate in architecture discussions and contribute to AI platform and solution design. • Document AI solutions, workflows, and implementation patterns to support long-term maintainability. • Stay current with advancements in AI technologies and recommend opportunities to improve engineering practices.

• Lead the definition of the enterprise Artificial Intelligence architecture, establishing standards, frameworks and best practices for AI, Generative AI and Machine Learning solutions on Google Cloud Platform (GCP). • Design scalable architectures for applications based on Large Language Models (LLMs), Generative AI, RAG (Retrieval-Augmented Generation), intelligent agents (AI Agents) and multimodal systems. • Define standards for development, integration, deployment, monitoring and governance of AI solutions, ensuring scalability, security, observability and high availability. • Serve as the technical reference across business areas, Data Engineering, Data Science, Analytics, Software Engineering and Technology, translating business challenges into AI-based solutions. • Design architectures for virtual assistants, copilots, semantic search engines, intelligent automation, document processing, recommendation, classification and summarization using Generative AI. • Define integration strategies between AI models, data platforms, APIs, microservices, enterprise systems (ERP, CRM, SAP and legacy systems) and business applications. • Lead the definition of architectures using Vertex AI, Gemini and other Google Cloud Platform AI services. • Design AI pipelines using best practices in MLOps, LLMOps, DataOps, CI/CD and infrastructure as code. • Define strategies for the evaluation, monitoring and continuous evolution of AI models, tracking metrics for quality, cost, performance, security and usage. • Ensure adherence to corporate policies on security, privacy, data governance and Responsible AI. • Support the evolution of the corporate AI platform by evaluating new technologies, frameworks and architectures aligned with market best practices. • Conduct technical assessments (As-Is and To-Be), proposing scalable architectures to accelerate the adoption of Artificial Intelligence in the organization. • Influence strategic decisions related to the evolution of the enterprise AI architecture, promoting innovation and driving business value.

• Provide technical leadership in the development of Artificial Intelligence, Generative AI and Machine Learning solutions using Google Cloud Platform (GCP). • Design and implement applications based on Large Language Models (LLMs), RAG (Retrieval-Augmented Generation), AI Agents, multimodal systems and intelligent assistants. • Develop AI application architectures using Vertex AI, Gemini and other Google Cloud Platform services. • Define technical standards for AI application development, promoting engineering best practices, component reuse, observability, scalability and security. • Develop data and AI processing pipelines, including ingestion, enrichment, indexing, embeddings, context retrieval and inference. • Implement solutions using vector databases, semantic search engines, embeddings and advanced information retrieval strategies. • Develop APIs, microservices and integrations between AI applications, data platforms, corporate systems and cloud services. • Work on building agent-based applications, Function Calling, Tool Use and orchestration of multiple agents. • Implement MLOps and LLMOps practices, including model versioning, monitoring, evaluation, observability, deployment automation and lifecycle management of applications. • Continuously evaluate new models, frameworks and AI technologies, proposing improvements for platform evolution. • Serve as a technical reference for the team, supporting code reviews, defining standards, troubleshooting and evolving solutions. • Collaborate with AI Architects, Data Engineers, Data Scientists, Product Owners and business areas to translate requirements into scalable solutions. • Ensure quality, performance, security and operational efficiency of developed applications.