Remote AI Solutions Field Engineer

ServiceNow; Greater London; Hybrid; GBP 120,000 - 180,000; Full time

Job summary

ServiceNow seeks an AI-native engineer to build production-grade, LLM-enabled applications that span backend logic, data orchestration, and front-end UI. You will work alongside customers in live environments to adapt, deploy, and iterate solutions, codifying reusable assets for future engagements.

Ideal candidates have 8+ years in software engineering and 3+ years building production ML/AI systems end-to-end, including retrieval-augmented generation, embeddings, and vector databases.

Qualifications

• AI fluency in practice—integrating AI into workflows, decision-making, and problem-solving.
• 8+ years of software engineering experience, including customer-facing or embedded roles.
• 3+ years building production ML/AI systems end to end: data prep through deployment, monitoring, iteration.

Responsibilities

• Deliver production-grade LLM-enabled applications spanning backend logic, data orchestration, and front-end UI.
• Collaborate with customers in live environments to deploy and iterate solutions.
• Codify reusable assets—libraries, prompts, scaffolds—for future engagements.
• Influence platform by sharing feedback with platform and product teams.

Skills

AI fluency

Software engineering

Backend development

Frontend development

APIs

LLM / AI systems

Distributed systems

Observability

MLOps / DevOps

Field readiness

Tools

LangChain/LangGraph

LlamaIndex

Semantic Kernel

PyTorch

TensorFlow

scikit-learn

Hugging Face ecosystem

OpenAI

Anthropic

Azure AI Foundry / Vertex AI

Job description

ServiceNow seeks an AI-native engineer to build production-grade, LLM-enabled applications that span backend logic, data orchestration, and front-end UI. You will work alongside customers in live environments to adapt, deploy, and iterate solutions, codifying reusable assets for future engagements.

Ideal candidates have 8+ years in software engineering and 3+ years building production ML/AI systems end-to-end, including retrieval-augmented generation, embeddings, and vector databases.