AI Governance & Information Protection Engineer

Infosys Limited

Raleigh (NC)

On-site

USD 140,000 - 180,000

Full time

3 days ago
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Job summary

Infosys Limited is seeking an Information Protection & AI Governance Engineer to drive governance, protection, and security operations for enterprise AI platforms. The role spans Purview administration, AI guardrails, and insider risk management across on-prem and cloud environments.

The ideal candidate will design, tune, and implement governance controls while collaborating with security, platform, and business teams to safely enable AI adoption in regulated contexts.

Qualifications

  • Experience designing and tuning AI governance controls and guardrails for enterprise AI platforms.
  • Experience developing insider threat detection strategies and policy tuning.
  • Knowledge of Microsoft 365 Security and related governance tooling.

Responsibilities

  • Collaborate with internal and client teams to resolve incidents and document findings with preventive recommendations.
  • Evaluate IT infrastructure and prepare actionable assessment reports for improvement opportunities.
  • Design scalable, cost-effective IT infrastructure solutions and develop technical documentation.
  • Coordinate deployments, release readiness, and post-deployment testing.
  • Develop automation and dashboards for compliance and insider risk programs.

Skills

Microsoft Purview
AI governance
Insider risk detection
Security engineering
Automation with PowerShell
Microsoft Graph API
KQL

Tools

Purview
PowerShell
Microsoft Graph API
KQL

Job description

Infosys Limited is seeking an Information Protection & AI Governance Engineer to drive governance, protection, and security operations for enterprise AI platforms. The role spans Purview administration, AI guardrails, and insider risk management across on-prem and cloud environments.

The ideal candidate will design, tune, and implement governance controls while collaborating with security, platform, and business teams to safely enable AI adoption in regulated contexts.

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