Network Researcher

Network research is at the core of how Armis works. As an agentless platform, everything we know about a device starts with the network - and this team owns that layer end to end.

You'll work across the full spectrum: IT, OT, IoT, medical, industrial. Researching protocols, dissecting traffic, and turning raw network data into accurate device insights at scale.

• →Own the deep packet inspection pipeline from initial protocol research through to production code.
• →Research network protocols and device behaviors - inspecting traffic, modeling architectures, and building the understanding that drives accurate client insights.
• →Develop core platform features based on network activity, from protocol parsers to device classification logic.
• →Dig into the security posture of devices and protocols at the network layer - identifying implementation flaws, documenting findings, and driving responsible disclosure.
• →Work closely with Product, Data, and other R&D teams.
• →Join customer POCs when it matters - debugging hard problems in time-sensitive environments.

• 5+ years of experience in network research and traffic inspection.
• 5+ years of Python development on production systems.
• Deep knowledge of network concepts, protocols, and infrastructures - across IT and ideally OT/ICS or medical environments.
• SQL and database fundamentals.
• Strong sense of ownership and the ability to operate on a tight schedule without losing rigor.
• Background in cybersecurity.

• Experience building features for large-scale distributed systems.
• Reverse engineering experience - binary analysis, protocol RE, Wireshark/Scapy-level dissection of undocumented protocols.
• Familiarity with threat and malware analysis - understanding attacker behavior at the network layer.

The network layer is where Armis starts and where the hardest problems live. You'll own meaningful pieces of it - researching protocols nobody has documented well, solving edge cases that matter to real enterprise and critical infrastructure environments, and shipping the results into a platform used at scale.