IAM AI Engineer

Introduction

Welcome to Gallagher - a global community of people who bring bold ideas, deep expertise, and a shared commitment to doing what’s right. We help clients navigate complexity with confidence by empowering businesses, communities, and individuals to thrive. At Gallagher, you’ll find more than a job; you’ll find a culture built on trust, driven by collaboration, and sustained by the belief that we’re better together. Whether you join us in a client-facing role or as part of our brokerage division, our benefits and HR consulting division, or our corporate team, you’ll have the opportunity to grow your career, make an impact, and be part of something bigger. Experience a workplace where you’re encouraged to be yourself, supported to succeed, and inspired to keep learning. That’s what it means to live The Gallagher Way.

Overview

The Identity and Access Management AI Engineer is responsible for designing, engineering, and operationalizing AI-enabled identity security capabilities across the enterprise. This role combines deep IAM engineering expertise with artificial intelligence, machine learning, automation, and analytics to strengthen identity controls, reduce access risk, improve operational efficiency, and detect emerging identity-based threats.

The engineer will help modernize identity services by applying AI to access governance, privileged access, authentication risk, identity lifecycle management, entitlement analysis, anomaly detection, and automated decision support. This includes helping deploy and operationalize the built-in AI capabilities expected in the next version of Identity Manager. This position partners closely with IAM, the Corporate AI Team, cyber defense, security architecture, infrastructure, cloud, data science, risk, compliance, and application teams to deliver secure, scalable, and compliant identity solutions.

How you’ll make an impact

• Design, build, and support AI-driven IAM capabilities that improve identity governance, access management, privileged access management, and authentication risk controls.
• Develop models, analytics, and automation that identify excessive access, toxic entitlement combinations, segregation of duties conflicts, dormant accounts, orphaned identities, risky privileged access, and abnormal authentication behavior.
• Apply machine learning, rules-based analytics, and graph-based identity intelligence to detect access anomalies and recommend remediation actions.
• Engineer AI-assisted workflows that support access request reviews, entitlement certification, role mining, policy recommendations, and identity lifecycle decisions.
• Partner with IAM platform owners to integrate AI capabilities into identity governance, access management, PAM, directory, and cloud identity tools.
• Lead or support deployment, configuration, governance, and adoption of built-in AI capabilities delivered in the next version of Identity Manager.

Identity Governance and Access Intelligence

• Enhance identity governance processes through automated access insights, risk scoring, peer-group analysis, and entitlement usage analytics.
• Support role-based access control, attribute-based access control, policy-based access control, and least-privilege access models using data-driven recommendations.
• Design and tune access risk models that prioritize remediation based on business criticality, privilege level, account type, data sensitivity, and user behavior.
• Improve access certification campaigns by reducing reviewer fatigue, identifying low-risk approvals, and surfacing high-risk exceptions for focused review.
• Develop reporting and dashboards that provide IAM leadership, risk teams, auditors, and application owners with actionable identity risk insights.

AI Security and Responsible AI Controls

• Embed security, privacy, and responsible AI principles into IAM AI solutions from design through production operations.
• Assess AI-enabled identity use cases for risks such as data leakage, prompt injection, model misuse, biased recommendations, excessive automation, and unauthorized access to sensitive identity data.
• Implement controls for model access, prompt governance, data minimization, audit logging, approval workflows, and human-in-the-loop decision-making.
• Collaborate with legal, privacy, compliance, and risk stakeholders to ensure IAM AI solutions align with internal policies, regulatory obligations, and industry framewor…