Director, Cloud & AI Security

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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.

• 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

• 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/Sage Maker, 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 Hashi Corp 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)

• Production experience deploying agentic AI systems with secure tool chains, 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

S&P Global states that the anticipated base salary range for this position is $200,000 to…