Member of Technical Staff - Distributed Systems
Listed on 2026-07-15
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IT/Tech
Cybersecurity, AI Engineer (Applied/Software), Cloud Computing: Infrastructure & Operations
About Us
At Armadin, we're a group of engineers, researchers, and hackers on a mission to redefine what proactive security can do in the AI era. Cyberattacks are becoming autonomous and relentless and we believe defending against threats before they materialize is one of the most powerful ways to protect the institutions the world depends on.
We're building autonomous proactive security from the ground up, reinforcing the tradecraft of elite red teamers into purpose-built security models and agents that discover risk and remediate it before organizations are breached.
Led by Kevin Mandia, founder of Mandiant ($5.4B exit to Google), our team brings together researchers and engineers from Google, xAI, Meta, Stanford, and MIT to reinvent security for an adversary that never sleeps.
What You ll DoDesign Core Systems: Architect the services, pipelines, and storage engines powering our platform and autonomous agents.
Scale for AI: Build high-throughput, low-latency infrastructure that scales with data, customers, and agentic workloads.
Own Production: Take end-to-end responsibility for the reliability, performance, and cost of critical systems.
Empower Teams: Build the platforms and tooling that let agentic and product teams ship fast.
Solve Hard Problems: Go deep on consistency, concurrency, fault tolerance, and latency.
Systems Depth: Strong fundamentals in backend infrastructure and scalable production systems.
Battle-Testing: Experience operating at scale and navigating failure modes and bottlenecks.
Execution: You turn ambiguous problems into shipped, rock-solid software.
Ownership: Comfort spanning architecture to implementation and rollout.
AI Fluency: You build with AI natively and want to build the infrastructure behind it.
Collaboration: You work across boundaries and care about the outcome, not just your slice.
Cloud infrastructure (GCP, AWS, Azure), containers, Kubernetes.
Real-time streaming and large-scale storage.
Infrastructure for AI/ML workloads (inference, model serving, data systems).
Enterprise products built for security, scale, and trust.
In-person in our Palo Alto office.
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