Agentic AI Governance Lead

Job Description The Agentic AI Governance Lead is responsible for establishing enterprise-wide governance for AI agents operating across platforms, clouds, business functions, and autonomous workflows. This role provides the visibility, accountability, standards, and intervention paths needed to govern agent behavior in alignment with company policies, enterprise technology standards, and applicable regulatory obligations. The position serves as a central governance point for agent registration, decision traceability, runtime risk management, cross-platform standards alignment, use case review, cost prediction, incident response, and governance reporting. The Leader will partner closely with AgentOps, Cybersecurity, Architecture, platform teams, and business stakeholders to define controls, monitor agent risk, identify escalation paths, and ensure production agents remain transparent, auditable, and accountable. Success in this role requires strong systems thinking, practical knowledge of agentic AI concepts, experience translating standards into operational processes, and the ability to influence teams without direct authority. The ideal candidate understands how agents interact with identity, data, platforms, APIs, business processes, and policy, and can convert that understanding into clear governance routines, dashboards, decision trees, and response protocols. We are seeking an Agentic AI Governance Lead to provide enterprise-wide governance, visibility, accountability, and intervention capabilities for AI agents operating across platforms, clouds, business functions, and autonomous workflows. The position is focused on governance of agent behavior in compliance with company policies and applicable regulations. Key Responsibilities

• Agent Registry Management - ensure every production agent is registered and accountable, aligned to established agentic standards. This includes transparency in agent owners, platforms, related use cases, connected MCP servers and APIs, allowed skills and actions, accessible tools and endpoints, and connected data.
• Action Monitoring & Decision Traceability - establish agent decision auditability according to enterprise standards and applicable regulatory compliance obligations, including oversight of logging and review of: agent decisions, agent actions, system changes, external communications, API/MCP calls, and data transactions.
• Runtime Risk Management - partner with AgentOps to define alerts, monitor, and audit agents for alignment drift, unauthorized behavior, excessive autonomy, cost anomalies, data misuse, and policy violations. Define escalation paths to follow when thresholds are exceeded, including pause criteria, shutdown criteria, and human override requirements.
• Cross-Platform Agentic Governance - serve as the primary point of contact to apply consistent Technology standards (AI Governance, Architecture, Cybersecurity, and AgentOps) for agents across all platforms. Assess platforms with agentic capabilities for overall risk surface to determine appropriate governance steps needed, per documented standards.
• Agentic Use Case Review - review agentic use cases to identify runtime governance requirements in alignment with established standards and risk assessments. Establish decision trees for agentic use cases to assess best-fit and determine consistent paths to redirect to other options when appropriate.
• Agentic Cost Prediction - create standards for delivery teams to assess projected consumption-based cost estimates for their agentic workflows.
• Agent Incident Response - serve as the primary point of contact from AI Governance to partner with Cybersecurity and other stakeholders in response to incidents arising from agentic use.
• Agentic Governance Analytics & Reporting - create an enterprise agentic governance dashboard to provide visibility to total counts of agents, agent density per platform, and where the Company has the highest potential agentic risk exposure based on actions, incidents, and costs.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to View email address on click.appcast.io learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: Skills and Requirements Required Qualifications

• Years of Experience: 2+ Years of AI Governance Experience in additional to an extensive background in Data Governance prior
• Experience in agent orchestration concepts, including MCP architecture, APIs and integrations, AI agents vs copilots, Human-in-the-loop controls, agent autonomy levels, AI evaluation concepts, and Agent observability concepts.
• IT business analyst experience, preferably in a large complex fortune 500/100 organization, including the ability to synthesize established standards to define decision trees, escalation paths, dashboarding requirements, and operational agentic auditability.
• Familiarity with AI governance frameworks and regulations, with curiosity and openness to continuous learning in this space.
• Systems thinking mindset, understanding the connected ecosystem of agents, platforms, identity, data, business process, regulations, and policy.

Exceptional communication and teamwork skills, with demonstrated experience on high performing teams in a fast-paced environment; capable of handling ambiguity with confidence and capable of influencing stakeholder teams without direct authority. · Experience with telemetry, logging, alerting, monitoring, and incident management.

• Hands-on experience with agentic AI patterns - tool-use architectures, agent orchestration frameworks, or standard agent protocols.
• Hands-on development experience in any domain, with AI/ML/agentic development a plus.
• Experience working with enterprise AI architecture standards or working within platform teams.
• Conversational in AI security fundamentals such as agent identity, least privilege, external endpoints, and incident response.
• Literate in Data Governance concepts.

Domain experience in airline operations, travel, or logistics is a plus. Insight Global