Forward Deployed Software Engineer – Applied AI FDE

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.

Job Description

Team Bio: 

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 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 value—not 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 build—owning 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 innovation—delivering 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 stack—and 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 don’t just debug code—you 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 assets—libraries, prompts, scaffolds—to accelerate future engagements 
• Shape developer experience by sharing feedback with platform and product teams  

What You’ll Do: 

• Deliver end-to-end builds in agile sprints—from architecture to deployment in production 
• 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 things—shaping 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: 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