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Member of Technical Staff - Distributed Systems

Armadin Security - Palo Alto, CA, United States - In-office - posted 2026-10-05

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Armadin Security is building autonomous proactive security systems for the AI era, founded by Kevin Mandia (founder of Mandiant, acquired by Google for $5.4B). The team includes engineers and researchers from Google, xAI, Meta, Stanford, Georgia Tech, Waterloo, Berkeley, and MIT. In this Member of Technical Staff role, you will architect and build the core distributed systems powering Armadin's platform and autonomous security agents. Your responsibilities include: - Designing and architecting services, pipelines, and storage engines that form the backbone of the platform - Building high-throughput, low-latency infrastructure capable of scaling with data volume, customer growth, and agentic workloads - Taking end-to-end ownership of production systems, including reliability, performance, and cost optimization - Creating platforms and tooling that enable product and agentic teams to ship quickly - Solving complex distributed systems problems around consistency, concurrency, fault tolerance, and latency You will work across the full stack from architecture through implementation and production rollout, collaborating with security researchers, product teams, and other engineers to deliver rock-solid infrastructure. QUALIFICATIONS & REQUIREMENTS: - Strong fundamentals in backend infrastructure and scalable production systems - Proven experience operating systems at scale, with hands-on knowledge of failure modes and bottlenecks - Demonstrated ability to turn ambiguous problems into shipped, production-grade software - Comfort spanning architecture, implementation, and rollout - Native fluency building with AI and desire to build infrastructure behind AI/ML systems - Strong collaboration skills and focus on outcomes across team boundaries Preferred qualifications: - Experience with cloud infrastructure (GCP, AWS, Azure), containers, and Kubernetes - Real-time streaming and large-scale storage systems - Infrastructure for AI/ML workloads including inference, model serving, and data systems - Background building enterprise products focused on security, scale, and trust

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