Senior AI Security Engineer; Offensive & Infra Security

Requirements

• 8-10 years of deep hands-on experience in offensive security, including manual penetration testing, red team operations, and adversary simulation
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• Familiarity with modern C2 frameworks (e.g., Cobalt Strike, Sliver, Havoc), exploit development, and security research
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• Strong expertise across the AI/ML stack, including MLOps, inference architectures, vector databases, RAG, and agentic frameworks (e.g., ReAct, Reflexion)
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• Experience building, deploying, and securing LLM pipelines and AI workflows in Kubernetes and/or bare-metal environments
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• Strong software engineering foundations with experience shipping production code in Go, Python, or Rust
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• Hands-on experience securing Kubernetes, containers, VMs, and CI/CD environments
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• Deep understanding of application security vulnerabilities, secure coding practices, and distributed system design
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• Demonstrated ability to lead complex, cross-functional security initiatives end-to-end
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• Strong communication skills with the ability to influence both engineering teams and executive stakeholders
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• (Desirable) Public contributions to offensive security or AI security research (talks, blogs, tooling, CVEs, etc.)
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• (Desirable) Experience building internal red team or adversary simulation programs
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• (Desirable) Background in high-performance computing, AI infrastructure, or cloud-native platform security
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• (Desirable) Experience designing policy-as-code frameworks at scale

• 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
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• 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
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• 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
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• Performing advanced manual penetration testing across complex applications, infrastructure, Kubernetes environments, and distributed microservice ecosystems
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• Leading offensive security initiatives including red team operations, adversary simulation, and security research
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• Securing AI/ML systems end-to-end, including LLM pipelines, vector databases, RAG architectures, and agentic workflows
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• Identifying and researching novel attack surfaces unique to LLMs and autonomous systems, contributing to internal and external AI security research
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• Influencing secure system design across the SDLC, embedding security into CI/CD pipelines, container images, and deployment workflows
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• Integrating and operationalizing security tooling (SAST, DAST, SCA, container scanning) and driving remediation of complex application-layer vulnerabilities
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• Building internal security guardrails such as hardened base images, reusable libraries, and policy-as-code frameworks
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• Developing production-grade security tooling and leading cross-functional security programs from design through deployment