Director, AI Security & Technology

WHAT YOU'LL DO:

• Lead AI Security Strategy: Define the company’s AI security vision and build the roadmap for protecting AI/ML models, data pipelines, and inference systems. 
• Model Risk Management: Identify and mitigate AI-specific threats like prompt injection, model leakage, data poisoning, and adversarial input risks. 
• Secure Model Development & Deployment: Embed security into the LLM lifecycle — from data sourcing and training through fine-tuning, deployment, and updates. 
• Governance & Compliance: Develop and enforce policies aligned with HIPAA, HITRUST, NIST AI RMF, and emerging AI regulations. Guide teams on responsible AI use. 
• Cross-Functional Governance Collaboration: Work closely with internal governance stakeholders and teams (e.g., product, IT, and platform teams) to align on shared ownership of AI risk mitigation. 
• AI Maturity & Readiness Evaluation: Lead an assessment of organizational maturity from a security lens - including skills, workflows, tools, and infrastructure - and drive a clear, actionable plan to close security gaps. 
• Enable Customer Deployment Security: Create security guidelines, patterns, and support for customers deploying our models in their own environments. 
• Monitor Emerging AI Threats: Stay current on AI vulnerabilities, red-teaming techniques, and global AI regulatory trends — and translate those into practical controls and guidance. 
• Collaborate Across Teams: Partner closely with ML, DevOps, product, and compliance teams to make security scalable and usable — without slowing innovation. 

WHAT YOU'LL NEED:

• 8+ years in information security with at least 2 years focused on AI/ML systems 
• Deep understanding of LLMs and AI-specific risks 
• Familiarity with securing MLOps workflows and model-serving infrastructure (e.g., GCP, Azure, AWS) 
• Experience with threat modeling and mitigating attacks on AI models (e.g., prompt injection, inversion, poisoning) 
• Knowledge of healthcare security requirements (HIPAA, HITRUST) and how they apply to AI/ML 
• Strong communication skills — able to educate, influence, and guide both technical and executive audiences 
• Experience working with or securing customer-hosted software solutions 

NICE TO HAVE:

• Hands-on experience red-teaming LLMs or building secure RAG (retrieval-augmented generation) systems 
• Understanding of AI-specific policy and regulation (e.g., EU AI Act, Executive Orders, NIST AI RMF) 
• Passion for shaping safe and ethical AI in a high-impact domain like healthcare