ServiceNow Developer

About the Role

We are hiring two professionals to help design and implement practical AI governance and agentic control capabilities on ServiceNow. The role combines ServiceNow platform experience with AI governance, control tower implementation and hands-on understanding of agents, workflows and enterprise integrations.

Good to know: ServiceNow experience is mandatory. ServiceNow AI Control Tower experience is a strong advantage, but not a hiring condition. Candidates who have built AI governance or control-tower solutions using custom frameworks or other enterprise platforms will also be considered.

Key Responsibilities

• Design and implement governance for AI systems, models, agents, prompts, datasets, tools and third-party AI services.

• Set up AI inventory, ownership, risk classification, approvals, controls, exceptions, evidence and lifecycle processes.

• Build governance workflows and dashboards on ServiceNow using platform data models, Flow Designer / Workflow Studio, integrations and case-management patterns.

• Govern agentic AI use cases, including agent identity, tool permissions, human approvals, execution boundaries, auditability and safe failure handling.

• Translate Responsible AI, security, risk and compliance requirements into practical controls that can be monitored and evidenced.

• Integrate ServiceNow with GRC tools, enterprise AI platforms, identity systems, model registries, data platforms and observability services.

• Work with risk, security, privacy, data, architecture and engineering teams to define clear ownership and operating processes.

Experience & Skills

• 5 to 10 years of overall technology experience with meaningful hands-on ServiceNow implementation experience.

• Experience in AI governance, Responsible AI, model risk, technology risk, GRC controls or enterprise control tower implementation.

• Good understanding of AI asset inventory and lifecycle management, including assessments, controls, evidence, exceptions, issues and monitoring.

• Hands-on understanding of agentic AI concepts such as agents, tools, orchestration, human-in-the-loop controls, authorization, evaluation and failure handling.

• Experience translating governance requirements into working workflows, data models, integrations, dashboards or case-management solutions.

• Working knowledge of enterprise identity and security concepts such as least privilege, OAuth / OIDC, service identities, role-based access and audit trails.

• Comfort with APIs and enterprise integration patterns including REST, webhooks and event-driven integration.