What You'll Do:

📍Design, implement, and maintain security controls across multi-cloud infrastructures 📍Work closely with R&D teams to understand constraints and risks in Agentic AI and Infrastructure 📍Design and implement runtime AI security controls (guardrails, filters, policy engines, gateways). 📍Build protections for LLM inference, agent tool execution, MCP / plugin frameworks, and RAG pipelines. 📍Implement prompt, input, and output inspection for abuse, jailbreaks, data leakage, and policy violations. 📍Secure Infrastructure, CI/CD pipelines, and automation workflows by embedding DevSecOps best practices 📍Conduct security reviews of product features, new technologies and ensure they meet security requirements. 📍Secure Kubernetes clusters and containerized workloads in production environments 📍Evaluate AI attack vectors (prompt injection, model poisoning, data exfiltration, jailbreaks, emerging attack patterns) and implement effective mitigations 📍Collaborate with other security teams to resolve security issues and implement security improvements. 📍Lead security projects and initiatives across Fireblocks environments to enhance the platform's security.

What You'll Bring:

📍At least 3 years of experience with AWS, GCP, or Azure 📍Experience working with Agentic AI platforms such as Onyx, Noma, Cyata, Pilar, AKTO, or similar enterprise Agentic AI, strong plus but not mandatory. 📍Strong knowledge and experience with DevSecOps practices 📍In-depth knowledge of security best practices and technologies, including encryption, identity and access management, and network security 📍Experience with securing Kubernetes

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