Principal Security Engineer – AI & Copilot Data Protection

About Northern Trust: Northern Trust, a Fortune 500 company, is a globally recognized, award-winning financial institution that has been in continuous operation since 1889.   Northern Trust is proud to provide innovative financial services and guidance to the world’s most successful individuals, families, and institutions by remaining true to our enduring principles of service, expertise, and integrity. With more than 130 years of financial experience and over 22,000 partners, we serve the world’s most sophisticated clients using leading technology and exceptional service. Role Summary Seeking a Principal‑level individual contributor  to lead the secure enablement of Microsoft 365 Copilot and enterprise AI capabilities within Northern Trust's Cyber Team.  This role owns the end‑to‑end technical strategy, architecture, and operationalization of AI‑driven data protection and compliance controls  across Microsoft Purview, Defender, and M365 security services.  The Principal serves as the organization’s deep technical authority on AI data protection , shaping control strategy, influencing platform configuration decisions, and institutionalizing durable safeguards that reduce AI‑driven data risk while enabling productivity at enterprise scale. This is a hands‑on role with architect‑level accountability : designing systems that will stand up to audit, regulatory scrutiny, and adversarial pressure as AI usage scales.   Scope of Accountability (Principal Expectations) This role is expected to: Own the technical vision and control strategy  for AI and Copilot data protection, not just implement features. Define durable, repeatable patterns  for securing LLM‑enabled workflows that other teams can adopt. Operate with wide autonomy, minimal oversight, and direct influence across Security, Compliance, Privacy, M365, and Risk . Anticipate risk before incidents occur , translating emerging AI threats into preventive controls. Serve as escalation point and design authority for complex or ambiguous AI security decisions. Key Responsibilities AI & Copilot Security Architecture Act as hands‑on technical lead and design authority  for Copilot and enterprise AI security controls across Microsoft Purview, Defender, and M365. Define and evolve the AI data protection reference architecture , mapping controls to AI threat models and regulatory expectations. Review and harden Copilot platform configurations, including: Web grounding and search behaviors Agents, plugins, and connectors Permission inheritance and identity context Transcripts, prompt history, and retention models Ensure controls are designed for default‑secure behavior , least privilege, and fail‑safe operation. Control Engineering & Operations Design, implement, and operate AI‑related controls spanning: Information Protection and labeling strategy DLP and Endpoint DLP (including AI‑specific scenarios) Insider Risk Management and Communication Compliance Data Lifecycle Management and retention enforcement DSPM for AI, including exposure detection and oversharing remediation Configure, deploy, troubleshoot, and operate controls across AD and EntraID environments. Support production changes through disciplined change management and approved deployment windows. AI Risk Detection, Monitoring & Response Define AI‑specific risk use cases , signals, and thresholds aligned to data exposure, misuse, and policy violation scenarios. Build monitoring, alerting, and automation for abnormal or high‑risk AI usage patterns . Develop operational runbooks that enable consistent response, investigation, and evidence preservation. Ensure solutions are audit‑ready, regulator‑defensible, and operationally sustainable . Governance & Institutionalization Translate AI threat models into policy‑aligned, enforceable technical controls . Partner with governance stakeholders to support: AI risk assessments Control mapping and documentation Decision logs and exception handling Executive and stakeholder reporting Contribute expert guidance to Copilot readiness, Zero Trust alignment, and broader AI governance initiatives. Track delivery and technical debt using Azure DevOps, establishing transparency and accountability. Copilot‑Focused Control Outcomes Define and enforce Copilot‑protected labels  for files, groups, sites, and content sources. Prevent unauthorized content ingestion and unintended grounding into AI prompts. Expand browser and endpoint DLP protections, including: Copy/paste and screen capture controls AI prompt and response handling Operationalize DSPM for AI to continuously reassess exposure and remediate oversharing. Establish durable workflows for AI‑related insider risk and communication compliance scenarios. Required AI Security Expertise Deep understanding of LLM security fundamentals and threat modeling , including: Data exposure risks Indirect and chained prompt injection Model‑mediated data exfiltration Practical mitigation strategies for: Prompt injection and prompt data leakage Over‑permissioned grounding sources Agent and connector misuse Experience securing agentic or tool‑augmented AI systems , including least‑privilege access and approval models. Strong grasp of AI governance concepts , including risk classification, control frameworks, and policy alignment. Ability to translate abstract AI risk into concrete, enforceable technical controls . Qualifications Bachelor’s degree or equivalent experience in cybersecurity, engineering, or a related field. Extensive hands‑on experience with Microsoft Purview and Microsoft Defender (including Cloud Apps). Strong background in data protection, DLP technologies, and enterprise information security. Proven scripting and automation capability (PowerShell, Python, Power Automate). Experience operating within formal incident, problem, and change management processes (e.g., ServiceNow). Preferred Experience & Certifications Deep