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CRDT Software Engineer

webAI - Remote - Remote - posted 2026-09-24

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webAI is building a distributed AI platform that brings computation to the edge, enabling secure, private AI deployment on consumer hardware without relying on centralized servers. The company's mission centers on keeping data and intellectual property private while scaling large AI models across heterogeneous environments. You will join the backend systems team as a Senior or Staff Engineer focused on distributed infrastructure. This role emphasizes CRDT (Conflict-free Replicated Data Type) experience and peer-to-peer networking—the posting notes this is functionally identical to their Peer-to-Peer Software Engineer role, but with CRDT as the primary technical focus. Key responsibilities include: - Design and implement advanced synchronization and networking systems for reliable AI operations across edge devices, cloud systems, and air-gapped environments - Architect robust data synchronization frameworks using content addressable storage, Merkle trees, and CRDTs - Lead performance tuning, debugging, and optimization under resource-constrained and intermittent connectivity conditions - Apply security-first design principles: threat modeling, secure key management, cryptographic integration - Collaborate with MLOps, Infrastructure, and Security teams to deploy AI in restricted or air-gapped systems - Contribute to cross-functional architectural design and documentation - Maintain rigorous testing, observability, and validation practices - Work with distributed hash tables, content identifiers, gossip protocols, DAGs, overlay networks, and NAT traversal as needed Development is in Rust; the team supports engineers ramping up on the language while working on these systems. The company emphasizes core values of Truth, Ownership, Tenacity, and Humility, seeking engineers genuinely excited about the mission of decentralized, edge-based AI infrastructure. Qualifications: - Required: Experience with CRDTs - Required: Experience with peer-to-peer or decentralized networking frameworks

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