Staff Product Security Engineer

Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster.

We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI.

We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services.

If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe.

We’re seeking a Staff Product Security Engineer with deep AI/ML security expertise to strengthen Crusoe’s security posture across applications, infrastructure, and distributed AI systems. This is a highly technical role focused on advanced penetration testing, AI/ML attack surface research, and building secure-by-design guardrails that engineering teams rely on.

You’ll operate at the intersection of offensive security, AI systems, and production engineering; owning security outcomes end-to-end while influencing system design across the organization.

• Performing advanced manual penetration testing across complex applications, infrastructure, Kubernetes environments, and distributed microservice ecosystems

• Leading offensive security initiatives including red team operations, adversary simulation, and security research

• Securing AI/ML systems end-to-end, including LLM pipelines, vector databases, RAG architectures, and agentic workflows

• Identifying and researching novel attack surfaces unique to LLMs and autonomous systems, contributing to internal and external AI security research

• Influencing secure system design across the SDLC, embedding security into CI/CD pipelines, container images, and deployment workflows

• Integrating and operationalizing security tooling (SAST, DAST, SCA, container scanning) and driving remediation of complex application-layer vulnerabilities

• Building internal security guardrails such as hardened base images, reusable libraries, and policy-as-code frameworks

• Developing production-grade security tooling and leading cross-functional security programs from design through deployment

• 8-10 years of deep hands-on experience in offensive security, including manual penetration testing, red team operations, and adversary simulation

• Familiarity with modern C2 frameworks (e.g., Cobalt Strike, Sliver, Havoc), exploit development, and security research

• Strong expertise across the AI/ML stack, including MLOps, inference architectures, vector databases, RAG, and agentic frameworks (e.g., ReAct, Reflexion)

• Experience building, deploying, and securing LLM pipelines and AI workflows in Kubernetes and/or bare-metal environments

• Strong software engineering foundations with experience shipping production code in Go, Python, or Rust

• Hands-on experience securing Kubernetes, containers, VMs, and CI/CD environments

• Deep understanding of application security vulnerabilities, secure coding practices, and distributed system design

• Demonstrated ability to lead complex, cross-functional security initiatives end-to-end

• Strong communication skills with the ability to influence both engineering teams and executive stakeholders

• Public contributions to offensive security or AI security research (talks, blogs, tooling, CVEs, etc.)

• Experience building internal red team or adversary simulation programs

• Background in high-performance computing, AI infrastructure, or cloud-native platform security

• Experience designing policy-as-code frameworks at scale