Staff Cyber Security Engineer – AI Data Protection
Job Description Summary
This role sits within GE HealthCare ’s Cyber Data Protection team and owns the Data Loss Prevention (DLP) platforms used to manage AI-related data risks.
The successful candidate will work across Cyber and IT teams to secure enterprise AI adoption, reduce data leakage risk, and enable responsible AI use.
This hands-on engineering role requires expertise in AI technologies, automation, cloud, network, and SIEM platforms. Job Description
Roles and Responsibilities :
In this role, as part of the global Cyber Data Protection team, you will:
Platform Ownership – DLP for AI Threats -
- Own and operate the AI DLP platform, including administration, configuration, policy management, tuning, upgrades, deployments, and platform health.
- Engineer and deploy DLP and AI protection capabilities across endpoint, cloud, mobile, and network environments.
- Maintain detection policies, risk scoring, thresholds, baselines, operational metrics, and the service roadmap.
- Evaluate emerging DLP and AI security technologies through proof-of-concepts and platform assessments.
- Manage vendor performance, SLAs, incident resolution, and end-user issue triage through to closure.
AI Security & DLP Risk Management -
- Assess and manage AI-related data protection risks across Cyber, IT, and business teams.
- Evaluate emerging AI platforms for DLP, privacy, and compliance risks, and recommend appropriate controls.
- Define and implement AI guardrails to prevent data leakage, policy violations, and unsafe usage.
- Partner with AI enablement and governance teams to align solutions with data protection requirements.
- Monitor AI threats, including LLM, generative AI, and shadow AI risks.
Technical Engineering & Automation -
- Automate DLP workflows, triage, and integrations using Python, PowerShell, KQL, and Bash.
- Build Azure automation, SIEM queries, dashboards, and alerts using Logic Apps, Azure Functions, Automation Accounts, KQL, and Microsoft Sentinel.
- Support Windows and Mac endpoints for DLP deployment, enforcement, and troubleshooting.
- Apply cloud security controls across Azure, AWS, M365, IaaS, PaaS, and SaaS environments.
AI Enablement & Awareness -
- Stay current on AI developments, tools, agentic frameworks, and monitoring platforms relevant to data protection.
- Guide internal teams on the secure use of AI within IT and Cyber operations.
- Champion responsible AI adoption by identifying security gaps and recommending risk-based controls.
Stakeholder Engagement & Collaboration -
- Partner with DLP, Cyber, AI, and IT stakeholders to align platform capabilities with business priorities.
- Communicate platform status, risks, roadmap, and priorities clearly to leadership and stakeholders.
Education Qualification:
Bachelor’s degree in computer science or STEM Majors (Science, Technology, Engineering and Mathematics) with advanced technical experience.
Desired Characteristics:
Technical Expertise -
- Experience owning enterprise DLP or data protection platforms, including Microsoft Purview, Defender, Sentinel, or similar tools.
- Hands-on knowledge of AI security tools, agentic AI frameworks, and AI monitoring platforms.
- Proficiency in Python, PowerShell, Bash, KQL, SIEM analytics, and Azure automation.
- Strong understanding of cloud security, AI/ML risk, privacy, compliance, identity, networking, endpoints, and infrastructure security.
- Knowledge of CI/CD, DevSecOps, agile delivery, and relevant cyber security certifications is beneficial.
Leadership & Collaboration -
- Able to collaborate across Cyber, IT, business, and vendor teams in a global environment.
- Strong communicator who can influence stakeholders and present clearly to technical and leadership audiences.
- Experience managing vendors, SLAs, priorities, and mentoring junior team members.
Personal Attributes -
- Self-starter who takes ownership, learns quickly, and stays current on AI and data protection