Peer to Peer Systems Engineer

webAI•Washington, DC

About The Position

We are looking for engineers to support webAI’s Public Sector initiatives focused on secure, distributed, and resilient AI infrastructure. Ultimately for this team we’re looking for a Systems Engineer that knows Rust, or a Systems-ish Engineer that knows P2P very well. This role is more focused on Peer to Peer Engineering work. Here’s where it’s tricky. We know decentralized systems and distributed systems have a lot of overlap, but they aren’t exactly the same thing. In our opinion decentralized systems have a connotation of trustless environments, and that’s the knowledge we are looking for in this role. Taking it a step further of what would be great to have in this role, is experience developing tech that looks more like IPFS, torrents, etc. than blockchain, but we also know a lot of those concepts overlap too.

Requirements

5+ year of experience with backend systems languages (i.e. C++, Java, Go, etc.)
Active US Security clearance or eligibility and willingness to obtain a US Security clearance
Experience with peer to peer or decentralized networking frameworks

Responsibilities

Work in backend systems languages to design and implement advanced synchronization and networking systems that enable reliable AI operations across heterogeneous environments, from edge devices to cloud isolated government systems, while upholding the highest standards of performance, reliability, and data privacy.
Architect robust data synchronization frameworks using content addressable storage, Merkle trees, CRDTs, and erasure coding
Implement and optimize network protocols and routing mechanisms, including NAT traversal, VPNs, and multi protocol mesh topologies.
Lead performance tuning, debugging, and optimization of distributed software under resource constrained and intermittent connectivity conditions.
Ensure security first design through threat modeling, secure key management, and integration of cryptographic primitives and protocols.
Collaborate with MLOps, Infrastructure, and Security teams to deploy and integrate AI components in restricted or air gapped systems.
Contribute to cross functional architectural design discussions and documentation for internal and external (public sector) stakeholders.
Maintain rigorous testing, observability, and validation practices to ensure system reliability and compliance readiness.