ServiceNow

Staff Software Engineer - Agentic Workflow

ServiceNow Role Type:
ServiceNow Modules:
Department - JobBoardly X Webflow Template
DevOps
ServiceNow Certifications (nice to have):

Job description

Date - JobBoardly X Webflow Template
Posted on:
 
October 24, 2025

ServiceNow is seeking a Staff Agentic Software Engineer to lead the design and engineering of next-generation AI agentic workflows within the ServiceNow Global Cloud Services OODP Team. This role focuses on building scalable, reliable, and intelligent agent-driven processes for AI-powered observability, working closely with product, architecture, and engineering teams.

Requirements

  • Experience in leveraging critical thinking about how to integrate AI into work processes.
  • Proven experience designing and deploying LLM-powered workflows or AI agents in production environments.
  • Strong expertise in agentic AI orchestration frameworks and familiarity with planner-executor and multi-agent architectures.
  • 8 years of experience in software engineering with a track record of delivering high-quality products.
  • Bachelor's or 6 years with a Master with 3 years experience; or equivalent experience.
  • Strong Java, Python and REST API, backed by strong computer science fundamentals.
  • Strong data background with RDBMS and TSDB, and proficiency in analytical SQL and PromQL queries.
  • Expertise in CI/CD pipelines, containerization (Kubernetes, Docker), and cloud-native deployment for AI-driven services.
  • Excellent troubleshooting, debugging, and performance optimization skills.
  • Strong collaboration and cross-functional communication skills
  • Strong statistical background with ability to design scalable, robust, and efficient ML systems

Benefits

  • Collaborative culture
  • Continuous learning
  • Shared success

Requirements Summary

8+ years software engineering experience, strong AI orchestration skills, Java/Python proficiency, and data background. Bachelor's degree or equivalent is required. Must be proficient with CI/CD and cloud-native deployments