AI Security Engineer - Fireblocks

Track new developments, capabilities, and attack techniques in the AI space, and translate them into concrete risks for Fireblocks. Build and maintain a living threat model for AI usage across the company, covering the platform, internal tooling, and third-party AI services. Analyze how AI is used across Fireblocks - in the platform, by developers (e.g., coding assistants), by corporate and business users, and through AI tools brought in via procurement. Assess the configuration and security posture of AI systems and tools in use, and identify and prioritize gaps. Design and propose new tooling, configurations, and projects that reduce AI-related risk. Architect and implement the resulting solutions end-to-end, partnering with engineering teams where needed. Build and operate the AI security infrastructure that makes AI usage across Fireblocks secure by default. Research open-weight model implementations for use in security workflows. Deploy open-weight models to support the incident response teams in investigating and responding to security incidents in real time. 3+ years of experience spanning AI/ML, with hands-on exposure to both.\ 3+ years of experience in engineering / RnD roles. Strong knowledge of cloud infrastructure (AWS in particular) and how AI workloads run in production. Strong understanding of AI/ML system architecture - model deployment, inference infrastructure, RAG, pipelines, and agent frameworks. Hands-on experience configuring and rolling out leading AI tools and platforms for a broad internal audience. Experience working with open-weight/open-source models in production or research settings. A genuine builder mentality - a track record of designing, shipping, and operating security tooling or infrastructure end-to-end, not just advising on it. Excellent communication skills and the ability to work independently while coordinating closely with Security, R&D, and other stakeholders. Familiarity with AI security frameworks such as the OWASP Top 10 for LLM Applications, NIST AI RMF, or MITRE ATLAS. Experience with SOC/IR tooling, threat intelligence, or offensive security.

Fireblocks is expanding its security organization to meet the risks and opportunities created by the rapid adoption of AI - both inside the company and across our platform. As our AI Security Engineer, you will own the security lens on AI at Fireblocks: tracking the fast-moving external AI threat landscape, assessing how AI is actually being used across the company - in our platform, by developers, by corporate and business users, and through procured AI tools - and architecting and building the controls, infrastructure, and tooling that keep that usage secure. This is a hands-on, builder-focused role. You won’t just recommend solutions - you will design, implement, and operate them, working closely with Security, R&D, and other stakeholders across the business. You’ll also research how open-weight models can be put to work for us, building tooling that helps our incident response teams investigate and respond to threats in real time.

Track new developments, capabilities, and attack techniques in the AI space, and translate them into concrete risks for Fireblocks. Build and maintain a living threat model for AI usage across the company, covering the platform, internal tooling, and third-party AI services. Analyze how AI is used across Fireblocks - in the platform, by developers (e.g., coding assistants), by corporate and business users, and through AI tools brought in via procurement. Assess the configuration and security posture of AI systems and tools in use, and identify and prioritize gaps. Design and propose new tooling, configurations, and projects that reduce AI-related risk. Architect and implement the resulting solutions end-to-end, partnering with engineering teams where needed. Build and operate the AI security infrastructure that makes AI usage across Fireblocks secure by default. Research open-weight model implementations for use in security workflows. Deploy open-weight models to support the incident response teams in investigating and responding to security incidents in real time. 3+ years of experience spanning AI/ML, with hands-on exposure to both.\ 3+ years of experience in engineering / RnD roles. Strong knowledge of cloud infrastructure (AWS in particular) and how AI workloads run in production. Strong understanding of AI/ML system architecture - model deployment, inference infrastructure, RAG, pipelines, and agent frameworks. Hands-on experience configuring and rolling out leading AI tools and platforms for a broad internal audience. Experience working with open-weight/open-source models in production or research settings. A genuine builder mentality - a track record of designing, shipping, and operating security tooling or infrastructure end-to-end, not just advising on it. Excellent communication skills and the ability to work independently while coordinating closely with Security, R&D, and other stakeholders. Familiarity with AI security frameworks such as the OWASP Top 10 for LLM Applications, NIST AI RMF, or MITRE ATLAS. Experience with SOC/IR tooling, threat intelligence, or offensive security.