ServiceNow
Director, Forward Deployed Solutions Engineer Applied?AI FDE
ServiceNow, Santa Clara, California, United States, 95050
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. 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. 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. 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. 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 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 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.
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. 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. 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. 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. 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 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 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.