Forward Deployed Solution Engineer- Applied AI

ServiceNow • Santa Clara, CA

15h • Hybrid

About The Position

ServiceNow, founded in 2004 in San Diego, California, is a global market leader providing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Their intelligent cloud-based platform connects people, systems, and processes to empower organizations to work smarter, faster, and better. The Applied AI Forward Deployed Engineering (FDE) team partners with strategic customers to shape the future of enterprise AI, identifying high-value opportunities, accelerating business outcomes, and building reusable AI-native solutions that advance the Now AI Platform. The team's mission is to build intelligent, scalable AI solutions for mission-critical challenges by embedding in real-world complexity, delivering fast, iterating with purpose, and transforming successes into reusable patterns. This role is crucial as enterprises demand business value from AI initiatives, requiring the transformation of cutting-edge LLM capabilities into resilient, secure, and scalable software. As a Senior Forward Deployed Software Engineer (FDSE), you will act as the CTO of the build, owning everything from backend services to LLM pipelines and front-end integrations. You will partner with customers in the field to design, implement, and deliver solution-ready builds in agile sprints, creating reference implementations for scalable GenAI in the enterprise, codifying patterns, shaping internal tooling, and accelerating innovation with battle-tested, production-ready systems. The ideal candidate is a systems-minded, AI-native engineer who ships real software, owns the full stack, and is motivated by elegant APIs, intuitive UIs, and scalable orchestration pipelines. You should think like a product-minded CTO, balancing creativity with pragmatism to deliver impact, and be able to embed deeply with customer teams, diagnose root problems, and architect AI-powered workflows that run at scale, debugging systems, context, and customer pain points.

Requirements

• 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
• 10+ 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

Nice To Haves

• 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

Responsibilities

• 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
• Deliver Production-ready solution 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

Benefits

• base pay of $201,300 - $352,300
• equity (when applicable)
• variable/incentive compensation
• health plans
• flexible spending accounts
• 401(k) Plan with company match
• ESPP
• matching donations
• flexible time away plan
• family leave programs

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed
• Number of Employees: 5,001-10,000 employees