Infrastructure Security Engineer - Remote

Job Title: Sr. Infrastructure Security Engineer

Job Type: Full-Time

Location: Remote

The Role

We’re looking for an infrastructure security engineer who thinks like a builder, not an auditor. You’ll design and evolve the security foundations of a fast-moving, AI-native organization—where the goal isn’t just to reduce risk, but to enable us to move faster safely.

This role sits at the intersection of systems engineering, security research, and applied automation.

What You’ll Do

• Architect security systems across AWS, GCP, and Azure that scale with rapid product iteration.
• Build automated guardrails and self-healing infrastructure to eliminate entire classes of vulnerabilities.
• Design and implement Zero Trust primitives—identity, access, and policy as code—from first principles.
• Develop Detection-as-Code pipelines, treating detection logic like production systems (versioned, tested, deployable).
• Explore and deploy AI-native approaches to threat modeling, anomaly detection, and incident response.
• Partner closely with engineering and research teams to embed security into the development lifecycle.
• Write clearly and think clearly—security decisions should be legible, reviewable, and composable.
• Continuously rethink assumptions and evolve our security posture as new threats and paradigms emerge.
  
  

• Deep experience securing distributed, multi-cloud systems (AWS, GCP, Azure).
• Strong programming ability (Python, Go, Rust, or similar) with a bias toward automation and systems thinking.
• Experience with Infrastructure as Code (Terraform, Pulumi, etc.) and integrating security into CI/CD pipelines.
• Strong understanding of identity systems, least privilege, and Zero Trust architectures.
• Familiarity with modern detection ecosystems (e.g., Sigma, Panther, GuardDuty, SCC) and signal quality challenges.
• A mindset that treats security as an engineering and systems problem—not compliance.
• Comfort working in a highly asynchronous, writing-heavy, and fast-paced environment.
  
  

• Experience securing Kubernetes and containerized workloads at scale.
• Contributions to open-source security tools or research.
• Experience applying or experimenting with AI/ML in security contexts.
• Strong opinions about how security should evolve in an AI-first world.