IT & Software

Forward Deployed Solution Engineer – Applied AI FDE

ServiceNow

London · Greater London · United Kingdom

Overview

In this role you will build production-ready, LLM-enabled applications for enterprise customers, spanning backend, data orchestration, and frontend UI. You will work in the field with customers to deploy and iterate live solutions, codify reusable assets, and influence platform tooling. Your work aims to deliver scalable, secure GenAI systems that translate business problems into practical, repeatable patterns. This position combines hands-on engineering with customer collaboration to accelerate transformation on the Now Platform.

Responsibilities
  • Build solution-ready LLM-enabled applications spanning backend logic, data orchestration, and frontend UI
  • Operate in the field with customers to adapt, deploy, and iterate in live environments
  • Codify reusable assets (libraries, prompts, scaffolds) to accelerate future engagements
  • Shape developer experience by feeding back to platform and product teams
  • Deliver end-to-end production-ready solutions in agile sprints
  • Engineer with versatility across APIs, orchestration pipelines, vector databases, LLM frameworks, and UI components
  • Navigate legacy systems and ambiguity while maintaining safe, rapid delivery
  • Contribute to shared SDKs, tools, and documentation to scale success across customers
  • Influence platform strategy through field-tested insights and extensible code
Key requirements
  • Extensive software engineering experience with AI into work processes or decision-making
  • 10+ years in software engineering; 2+ years in customer-facing or embedded roles
  • Proven design and implementation of AI-native software in production
  • Backend: Python, Node.js, Java; Frontend: React, Angular; APIs: REST/GraphQL
  • LLM tooling experience: LangChain, Semantic Kernel, prompt chaining, vector search, context management
  • Performance and observability: debugging distributed systems, latency tuning, monitoring
  • Platform mindset: contribution to shared SDKs and tooling
  • Product sensibility: user value focus, MVP iteration, scalability
  • DevOps fluency: deploying in AWS/Azure/GCP with CI/CD, containers, infrastructure as code
  • Field readiness: willing to travel up to 30% for onsite delivery
  • customer-facing collaboration
  • problem solving with systems thinking
  • clear communication and feedback to cross-functional teams
  • Python
  • Node.js
  • Java

Reference: WJ-747_30945621

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