Principal Security Engineer – GenAI Platform

Join Wolters Kluwer as a Principal Security Engineer on the GenAI Platform team and be part of a dynamic global technology company that makes a difference every day.

Wolters Kluwer provides expert software and information solutions that professionals rely on in critical moments. The company is focused on AI-powered solutions that combine deep domain knowledge, proprietary content, and advanced technology to provide expert-validated insights, automate workflows, and drive better outcomes.

About this role

Our team is building a central GenAI Platform to empower hundreds of product teams across the organization with scalable capabilities for rapid development, validation, and deployment of AI agents. We also drive the development of the most impactful AI agents, ensuring faster delivery and greater impact across multiple domains. With over 20 agents already launched and many more in progress, our work accelerates innovation and improves outcomes in critical industries.

You'll join a 100-engineer team within a larger organization that combines the stability of an established company with the agility of a startup. In this high-autonomy, high-impact role, you'll take problems from concept to production, mentor less experienced engineers, and lead by example.

Responsibilities

• Design and implement security for AI agents, full-stack apps, and platforms
• Build and maintain DevSecOps pipelines (SAST, SCA, DAST, secret scanning)
• Conduct threat modeling and enforce least-privilege access
• Lead security initiatives for flagship AI products (e.g., UpToDate Expert AI)
• Ensure compliance with SOC 2, HIPAA, ISO 27001
• Mentor engineers and promote a security-first culture
• Continuously improve security tooling and practices

Requirements

• 8+ years of cloud security engineering experience (AWS and/or Azure)
• Expert-level Python and Bash for security automation
• Deep experience with CI/CD security integration
• Strong background in threat modeling and security architecture
• Experience securing containerized environments (Docker, Kubernetes)
• Understanding of AI/ML security challenges

Preferred

• Relevant security certifications (AWS, Azure)
• Experience with large-scale distributed systems
• Familiarity with healthcare data security regulations
• Knowledge of LLM-specific security considerations

Your first months

• Month 1: Deep-dive into one platform component most aligned with your expertise; ship small improvements while ramping up.
• After onboarding: We’ll align on a high-impact area that fits your strengths and ambitions.