Job Description

Role:

This role requires a strong security and engineering background combined with AI/LLM development and deployment knowledge, preferably with deep knowledge of AI security principles. The focus will include evaluating AI protection and AI-SPM solutions, deployment and integration with enterprise cloud ecosystem, and enforcing and configuring centralized security policies.

High Level Requirements:

• Strong engineering, system architecture, and hands-on deployment/integration experience in the cloud (namely AWS).
• Strong understanding of AI security principles and best practices, with the ability to apply them in production environments.
• Familiarity with deploying and securing AI pipelines across cloud ecosystems (e.g., Databricks, AI Gateway).
• Experience configuring, integrating, and enforcing security guardrails across AI systems.
• Ability to define, implement, and operationalize AI security baselines, and evaluate AI security solutions (e.g., AI Runtime Protection, AI-SPM).
• Understanding of AI governance and regulatory requirements (GDPR, EU AI Act, …), with the ability to translate them into enforceable policies and controls.
• Ecosystem: AWS, Databricks, Bedrock, MLflow, n8n, UiPath, Terraform.

Experience Level:

• Senior Engineer / Security Engineer / Security Architect: ~5–7 years total experience
• Experience by Area:
  • Cloud (AWS): ~4–6 years – implementation and integration of secure architectures, not just used services
  • Security Fundamentals: ~2–4 years in security-focused work (can overlap with cloud role)