Senior AI Security Architect

Grayscale is seeking a Senior AI Security Architect to ensure the secure adoption of AI across the firm, focusing on designing security controls and governance for AI systems. Grayscale is the largest digital asset-focused investment platform in the world by AUM and offers the broadest selection of digital asset investment products in the U.S. based on number of products. Our platform spans the full spectrum of institutional-grade solutions—from single-asset exposures to diversified and thematic strategies—with a goal of providing every investor with access to the hyper-expanding digital asset universe. Our firm offers a rare combination of decades of traditional finance work experience and digital asset leadership that brings an institutional mindset to the maturing digital asset industry. This convergence of capabilities positions us to deliver investment solutions and client experiences that are both institutionally robust and technologically advanced, which we believe offers a competitive edge that is difficult to replicate. We’re proud of our deep crypto expertise and work closely with individual and institutional investors as they explore this asset class as part of their portfolio allocation.

• •Partner with engineering teams to design secure AI-enabled systems and define the security requirements, controls, and guardrails necessary for production deployment.
• •Develop and maintain AI security standards, reference architectures, and approved design patterns for AI-enabled applications, platforms, and workflows.
• •Lead threat modeling, architecture reviews, and security assessments for AI use cases, identifying risks such as prompt injection, data leakage, model misuse, and unintended agent behavior.
• •Define and implement controls to protect sensitive data, including access controls, data segregation, lifecycle management, logging, monitoring, and auditability requirements.
• •Establish security requirements for enterprise AI platforms, including model access, tool permissions, integration patterns, and third-party AI provider usage.
• •Define validation, monitoring, detection, and incident response requirements for AI-enabled systems and partner with engineering and security operations teams to ensure effective implementation.
• •Establish secure patterns for the use of AI throughout the software development lifecycle, including code generation, developer tooling, and AI-assisted engineering workflows.
• •Assess and manage technical and operational risks associated with AI systems and third-party providers, including exception management, risk acceptance, and regulatory alignment.
• •Partner with compliance, audit, and business stakeholders to ensure AI-enabled processes meet regulatory, control, and governance requirements.
• •Stay current on emerging AI security risks, technologies, frameworks, and best practices, helping shape Grayscale's long-term AI security strategy.