Sr. Delivery Acceleration AI Engineer

ServiceNow ServiceNow · Enterprise · Boston, MA +1 · Customer Outcomes

This role focuses on designing, developing, and optimizing AI-powered autonomous implementation solutions using LLMs and prompt engineering to automate ServiceNow configurations, generate implementation artifacts, and accelerate time-to-deploy. The engineer will build and refine AI agents that integrate with professional services workflows and the ServiceNow platform.

What you'd actually do

  1. Architect and build AI agent workflows that autonomously generate ServiceNow configurations, implementation plans, user stories, and test scripts from customer requirements
  2. Develop, test, and iterate sophisticated prompt chains and orchestration patterns that produce consistent, production-quality outputs across ServiceNow product workflows (ITSM, CSM, HRSD, SPM, etc.)
  3. Design multi-step agentic processes that handle complex implementation logic—scope validation, dependency mapping, configuration generation, and quality assurance—with minimal human intervention
  4. Serve as a subject matter expert in prompt engineering techniques for large language models, including chain-of-thought reasoning, few-shot learning, structured output generation, and context window optimization
  5. Design and execute systematic prompt evaluation frameworks that measure output accuracy, consistency, completeness, and adherence to ServiceNow implementation standards

Skills

Required

  • Prompt engineering
  • AI agent architecture
  • LLM systems
  • Large language models
  • Chain-of-thought reasoning
  • Few-shot learning
  • Structured output generation
  • Context window optimization
  • Prompt evaluation frameworks
  • Professional services delivery
  • ServiceNow configurations
  • ServiceNow platform
  • Agile/sprint cadence
  • API design
  • Data pipelines
  • Integration patterns

Nice to have

  • Solution architects
  • Product managers
  • Delivery consultants
  • Platform administrator
  • AI Architects

What the JD emphasized

  • Critically, you must understand the professional services go-to-market motion
  • rigorous quality validation
  • continuous experimentation
  • systematic prompt evaluation frameworks
  • enterprise quality standards

Other signals

  • AI agents
  • LLMs
  • prompt engineering
  • automation