Staff Product Security Engineer, Crusoe Energy Systems

• 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

Desirable

• 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