ServiceNow Manager

Key Responsibilities

AI Architecture, Engineering & Delivery

• AI Solution Engineering: Lead the end-to-end design, development, and deployment of AI-driven solutions across the ServiceNow platform.
• GenAI & Agentic AI Adoption: Drive the adoption of advanced platform capabilities, including Now Assist, AI Agents (Agentic AI), Predictive Intelligence, and AI Search.
• Modern Developer Tooling: Leverage ServiceNow Build Agent, IDE, and Fluent development frameworks to architect next-generation enterprise workflows.
• Hands-on Technical Leadership: Conduct technical solution architecture reviews, author proof-of-concepts (PoCs), perform code reviews, and guide complex platform implementations.

Governance, Strategy & Mentorship

• Engineering Standards & Responsible AI: Establish robust engineering best practices covering platform security, scalability, performance, data governance, and ethical AI frameworks.
• Process Embedding: Identify high-impact opportunities across business functions to embed AI automation directly into enterprise service management workflows.
• Team Development: Mentor, upskill, and guide software development engineers in adopting AI-first development practices and modern ServiceNow paradigms.

Requirements

Education & Experience

• Education: University degree in Information Technology, Computer Science, Software Engineering, or a related field.
• Platform Experience: Minimum of 5+ years of hands-on experience on the ServiceNow platform within software development, solution architecture, or engineering roles.
• Leadership Track Record: Proven experience leading or managing engineering, software development, or technical delivery teams is strongly preferred.

Technical & AI Competencies

• ServiceNow AI Mastery: Deep expertise in ServiceNow AI features, specifically Now Assist, Predictive Intelligence, and Agentic AI frameworks.
• Developer Ecosystem: Proficiency with ServiceNow Build Agent, IDE, and Fluent development tools.
• Governance & Security: Strong understanding of enterprise IT governance, security compliance, performance tuning, and Responsible AI principles.

Core Competencies

• Communication & Influence: Excellent stakeholder management and communication skills, with an ability to translate AI concepts into business outcomes.
• Innovation & Agility: Strong business acumen focused on continuous delivery excellence and workflow automation.