layiq

/la·yiq/adjective

worthy; deserving; fitting; suitable.

A role, opportunity, or path that merits attention, time, and pursuit.

Principal Security Engineer – AI & Copilot Data Protection at Northern Trust | LAYIQ

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 .

Principal Security Engineer – AI & Copilot Data Protection

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