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ServiceNow

Director, Forward Deployed Solutions Engineer Applied?AI FDE

ServiceNow, New York, New York, United States, 10001

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Director, Forward Deployed Solutions Engineer

Applied AI FDE

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

ServiceNow's 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 Platform. Our mission: We embed deeply with customers to build intelligent, scalable AI solutions for their most critical business challenges. By solving complex real-world problems at speed, we codify repeatable patterns that scale across the enterpriseinfluencing both customer success and the future of the platform. Enterprises are raising the bar. AI initiatives must deliver measurable business valuenot just theoretical promise. That requires turning cutting-edge LLM capabilities into resilient, secure, and scalable software systems that solve real-world problems. As a Director, Forward Deployed Software Engineer (FDSE), you lead high-performing engineering teams embedded with customers to deliver production-ready GenAI solutions. You provide technical direction, unblock delivery challenges, and ensure architectural integrity across the full stackfrom backend services and LLM pipelines to front-end integrations. Your leadership turns prototypes into reference implementations, accelerates innovation, and drives repeatable success across industries. You shape internal tooling, codify engineering patterns, and cultivate a culture of excellence and impact. You are a strategic engineering leader with deep systems thinking and a passion for building AI-native software at scale. You empower your teams to own the full stackbalancing elegant APIs, intuitive UIs, and scalable orchestration pipelines. You think like a product-minded CTO, guiding your engineers to deliver solutions that are both technically sound and business-aligned. You thrive in complex, customer-facing environments, helping your teams navigate ambiguity, diagnose root problems, and architect intelligent workflows that scale. You don't just debug codeyou coach engineers, debug systems, and align delivery with enterprise outcomes. You lead with empathy, foster collaboration, and elevate the technical bar across every engagement. You will: Lead teams building solution-ready applications: Guide engineering teams in developing LLM-enabled applications that span backend logic, data orchestration, and front-end UIensuring technical excellence and business alignment. Drive field execution: Oversee customer-embedded engagements, enabling your teams to adapt, deploy, and iterate solutions in live environments with agility and precision. Codify reusable engineering assets: Direct the creation of reusable libraries, prompt scaffolds, and modular components that accelerate future delivery and scale impact. Shape developer experience: Channel field insights into platform and product teams, influencing roadmap priorities and improving tooling for broader engineering adoption. What you'll do: Deliver end-to-end solutions through teams: Ensure your teams deliver complete buildsfrom architecture to production-ready deploymentwithin agile sprint cycles. Guide versatile engineering practices: Mentor engineers across the stackAPIs, orchestration pipelines, vector databases, LLM frameworks, and UI componentsfostering technical depth and adaptability. Enable agile execution: Help teams navigate legacy integrations, ambiguity, and high-stakes environments while maintaining speed and safety in delivery. Scale through codified patterns: Lead the development of scaffolds, SDKs, and documentation that enable repeatable success across customer engagements. Influence platform strategy: Translate field-tested insights into actionable feedback for product and platform teams, driving extensible improvements and innovation. What success looks like: Production-ready delivery: Your solution builds consistently convert to scaled deployments in production-ready 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. Qualifications

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 AI's potential impact on the function or industry. Relevant experience: 13+ 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-ready 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-ready 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 leadership powers transformation, your teams ship real-world systems, and your vision shapes how the future scales. For positions in this location, we offer a base pay of $236,000 - $413,000, 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.