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. \\\\Team Bio:\\\\ \\\\ServiceNows Applied AI Forward Deployed Engineering (FDE)\\\\ team is where bold ideas meet transformative action. We partner with our most strategic customers to shape the future of enterprise AI. Together, we identify high-value opportunities, accelerate business outcomes, and build reusable AI-native solutions that advance the Now AI Platform. \\\\Our mission:\\\\ We partner deeply with our customers to build intelligent, scalable AI solutions that solve their most mission-critical challenges. By embedding in real-world complexity, we deliver fast, iterate with purpose, and transform every success into reusable patterns that accelerate transformation across the Now Platform and the broader enterprise. \\\\Why This Role Matters:\\\\ Enterprises are raising the bar. AI initiatives must deliver business valuenot just promise potential. That means taking cutting-edge LLM capabilities and turning them into resilient, secure, and scalable software. As a \\\\Senior Forward Deployed Software Engineer (FDSE)\\\\ , you act as the CTO of the buildowning everything from backend services to LLM pipelines and front-end integrations. You partner with customers in the field to design, implement, and deliver solution-ready builds in agile sprints. Your software becomes the reference implementation for scalable GenAI in the enterprise. You codify patterns, shape internal tooling, and accelerate innovationdelivering systems that are battle-tested in production and scalable across industries. \\\\Who You Are:\\\\ You are a systems-minded, AI-native engineer who ships real software. You own the full stackand are equally motivated by elegant APIs, intuitive UIs, and scalable orchestration pipelines. You think like a product-minded CTO, balancing creativity with pragmatism to deliver impact. You embed deeply with customer teams, diagnose root problems, and architect AI-powered workflows that run at scale. You dont just debug codeyou debug systems, context, and customer pain points. \\\\You will:\\\\ \\+ Build solution-ready LLM-enabled applications that span backend logic, data orchestration, and front-end UI \\+ Operate in the field, working side-by-side with customers to adapt, deploy, and iterate in live environments \\+ Codify reusable assetslibraries, prompts, scaffoldsto accelerate future engagements \\+ Shape developer experience by sharing feedback with platform and product teams \\\\What Youll Do:\\\\ \\+ \\\\Deliver Production -\\\\ readysolution in agile end-to-end sprints \\+ \\\\Engineer with versatility:\\\\ APIs, orchestration pipelines, vector DBs, LLM frameworks, UI components \\+ \\\\Operate with agility:\\\\ integrate with legacy systems, navigate ambiguity, ship safely at speed \\+ \\\\Codify patterns:\\\\ build scaffolds, SDKs, and documentation to scale success across customers \\+ \\\\Influence platform:\\\\ inform product strategy through field-tested insights and extensible code \\\\What Success Looks Like:\\\\ \\+ \\\\Production-grade delivery:\\\\ Your solution builds consistently convert to scaled deployments in production environments \\+ \\\\Reusable impact:\\\\ You author libraries, prompts, and scaffolds that power multiple deployments and projects \\+ \\\\Platform influence:\\\\ Your work shapes internal tooling and is integrated into platform roadmap and primitives \\+ \\\\Velocity and precision:\\\\ You move fast without breaking thingsshaping resilient, secure systems in high-stakes contexts \\+ \\\\Engineering leadership:\\\\ You are trusted by architects, PMs, and customer teams to lead implementation from zero to one \\\\What You Bring:\\\\ \\+ \\\\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 AIs potential impact on the function or industry \\+ \\\\Relevant Experience:\\\\ 8+ years of software engineering, including 2+ years building systems in customer-facing or embedded roles \\+ \\\\System architecture:\\\\ Proven ability to design and implement AI-native software in production environments \\+ \\\\Engineering depth:\\\\ Strength in backend (Python, Node.js, Java), frontend (React, Angular), APIs (REST/GraphQL) \\+ \\\\LLM tooling:\\\\ Familiarity with LangChain, Semantic Kernel, prompt chaining, vector search, and context management \\+ \\\\Performance & observability:\\\\ Skilled in debugging distributed systems, tuning for latency, and implementing monitoring \\+ \\\\Platform mindset:\\\\ Can contribute to shared SDKs and tools, raising engineering velocity for the whole org \\+ \\\\Product sensibility:\\\\ Prioritize for user value, MVP iteration, and long-term scale \\+ \\\\DevOps fluency:\\\\ Experience deploying in AWS, Azure, or GCP with CI/CD, containers, and infra-as-code \\+ \\\\Field readiness:\\\\ Able to travel up to 30% to embed onsite and deliver where it matters \\\\Preferred Qualifications:\\\\ \\+ Experience integrating AI into SaaS platforms like ServiceNow or Salesforce \\+ Track record of production deployments in secure, regulated enterprise environments \\+ Contributions to dev experience tooling, frameworks, or reusable AI scaffolds \\\\Join us at the frontier of enterprise AIwhere your code powers AI transformation, your systems go live in the real world, and your ideas shape how the future scales.\\\\ \\\\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 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.

The role requires 8+ years of software engineering experience, with at least 2 years in customer-facing or embedded roles. A proven ability to design and implement AI-native software in production environments is necessary. Strengths in backend development with Python, Node.js, or Java, frontend development with React or Angular, and API experience with REST or GraphQL are expected. Familiarity with LLM tooling such as LangChain, Semantic Kernel, prompt chaining, vector search, and context management is required. Experience with performance and observability in distributed systems, as well as DevOps fluency in AWS, Azure, or GCP with CI/CD, containers, and infra-as-code, is also needed.