AI Security Engineer - Assistant Vice President / Vice President

About the Role iCapital is looking for an Assistant Vice President / Vice President, AI Security Engineer to join the Security Engineering team, within the Information Security organization. As iCapital's first dedicated AI Security hire, this is an opportunity to establish and lead the firm's AI Security Engineering practice as its subject-matter expert: defining how iCapital adopts AI safely across software development, its platform, and emerging agentic systems, and putting the standards, guardrails, and tooling in place to make that possible. The ideal candidate is an experienced security engineer with strong cloud security and hands-on AI security expertise from prior roles, who can architect from the ground up, build and maintain tooling directly, and partner cross-functionally across a regulated fintech environment. Responsibilities Define and lead iCapital's AI security strategy and secure-by-design standards, in partnership with iCapital's AI team, spanning AI-assisted development and AI/GenAI platform capabilities. Establish governance, monitoring, and controls for AI coding assistants and their MCP integrations, bringing visibility to how AI is used across the developer population. Conduct threat modeling and security design reviews of AI systems and integrations, mapping identified risks to established AI security frameworks. Design and implement AI guardrails, including prompt injection defenses, output validation, and data protection, and embed them into engineering workflows and CI/CD pipelines. Define security architecture for autonomous and semi-autonomous agents, including least-privilege tool access, agent identity, and human-in-the-loop controls for high-risk actions. Architect and assess the security of AI/ML workloads running on AWS. Build and operate agentic AI workflows that strengthen Security Engineering and InfoSec operations, such as alert triage, enrichment, and detection engineering. Partner with the SOC to build detection and response capabilities for AI-specific threats, such as anomalous agent behavior or misuse of AI-granted access. Advise and support Engineering, Platform, and DevOps teams on implementing secure AI practices, and collaborate with Risk and Compliance on AI security requirements and controls. Qualifications 6–8 years of experience in security engineering, security architecture, or application/cloud security, with demonstrated hands-on experience securing AI, ML, or GenAI systems. Strong knowledge of LLM and agentic system risks and mitigations (e.g., prompt injection, data and model poisoning, excessive agency, model supply chain) and of securing MLOps pipelines, familiarity with technical AI security frameworks such as the OWASP Top 10 for LLM Applications and MITRE ATLAS, and general working knowledge of AI risk management frameworks (e.g., NISTAI RMF, ISO 42001). Experience working in cloud-native environments and securing cloud-hosted AI/ML platforms, with AWS strongly preferred (e.g., Amazon Bedrock, Amazon SageMaker). Practical experience with AI developer tools (e.g., Claude, Copilot, GitHub Copilot), MCP integrations, and agentic AI architectures, including securing them, building them, or both. Proficiency in coding to build and maintain security automation, tooling, and integrations, with hands-on experience in Python and other scripting languages. Track record of building security standards or programs from the ground up and driving adoption across engineering teams. Relevant hands-on certifications are a plus, particularly AWS cloud and cloud security certifications, as well as AI security certifications from bodies such as GIAC, Practical DevSecOps, or Offensive Security. Commitment to staying at the forefront of AI security trends and emerging threats, with strong communication skills and the ability to influence stakeholders and drive initiatives to completion. We believe the best ideas and innovation happen when we are together. Employees in this role will work…