Director, Cloud & AI Security

The Team:

Our team is at the forefront of enterprise AI security innovation, responsible for designing and implementing cutting-edge security frameworks across multi-cloud environments. We operate in a collaborative, fast-paced environment where security excellence meets AI advancement, enabling secure-by-design solutions that drive business growth while maintaining the highest standards of risk management and compliance.

Responsibilities and Impact:

Define and operationalize comprehensive AI Security Strategy across multi-cloud environments (AWS, Azure, GCP, OCI) and on-premises systems, covering models, data pipelines, orchestration layers, and agent integrations
Establish and maintain enterprise AI Risk Framework aligned with industry standards (NIST AI RMF, ISO/IEC 23894) and regulatory requirements, ensuring compliance across SOC 2, ISO 27001, and sector-specific regulations
Perform critical Security Architecture Reviews for AI systems including hosted and self-hosted models, agentic AI systems (MCP, ACP, A2A patterns), RAG implementations, and vector database integrations
Design and implement advanced agent safety controls including sandboxing, least-privilege tooling, prompt injection defenses, and secure tool-use patterns for enterprise AI deployments
Lead AI Security Governance initiatives across Legal, Compliance, Privacy, and Risk teams while championing secure-by-design and privacy-by-design principles throughout the organization
Drive enterprise-wide adoption of AI security policies and standards, enabling engineering teams through playbooks, secure coding guidelines, and threat modeling workshops while maintaining rapid innovation pace

What We're Looking For:

Basic Required Qualifications:

10+ years of Information Security experience with 4+ years specializing in cloud security and 2+ years in AI/ML or LLMOps security implementations
Hands-on expertise with multi-cloud platforms including identity management, encryption services, and AI/ML services (such as AWS Bedrock/SageMaker, Azure OpenAI/ML, GCP Vertex AI, OCI Data Science)
Proficiency in security engineering technologies including Zero Trust architecture, policy-as-code frameworks (such as OPA, Conftest, or Sentinel), and secrets management platforms (such as HashiCorp Vault, AWS Secrets Manager, or Azure Key Vault)
Deep knowledge of AI/LLM technology stack including RAG patterns, vector databases (such as Pinecone, Weaviate, or FAISS), prompt engineering, and agent orchestration frameworks (MCP, ACP, A2A patterns)
Experience with threat modeling and offensive security testing specifically for AI systems, including prompt injection attacks and agent misuse scenarios
Strong understanding of privacy regulations and compliance frameworks impacting AI implementations (such as GDPR, CCPA, GLBA, and sector-specific requirements)

Additional Preferred Qualifications:

Production experience deploying agentic AI systems with secure toolchains, runtime isolation, and enterprise-grade safety controls in regulated environments
Expertise in advanced privacy-preserving technologies including confidential computing platforms (such as AMD SEV, Intel SGX, or Azure Confidential Computing), differential privacy, or federated learning implementations
Background in model risk management and AI governance including explainability frameworks, provenance tracking, watermarking technologies, and automated evaluation pipelines
Experience in financial services or highly regulated industries with demonstrated knowledge of sector-specific AI compliance requirements and risk management practices