Senior/Staff Forward Deployed Engineer -… at WebAI

About Us

At webAI we firmly believe that the future of AI lies in distributed processing at the edge, bringing computation closer to the source of data generation. Our mission is to build a future where local and private is the default, servers and data centers are optional. Where valuable data and intellectual property remain entirely private, enabling the deployment of large-scale AI models directly on standard consumer hardware without compromising the information embedded within those models. We are developing an end-to-end platform that is secure, scalable, and fully under the control of our users, empowering enterprises with AI that understands their unique business.

About the Role

We are looking for Senior Engineers to drive webAI Public Sector initiatives focused on secure, resilient, and distributed data systems operating at the tactical edge.

In our world, network connectivity isn't guaranteed. Systems must thrive in Denied, Degraded, Intermittent, and Limited (DDIL) bandwidth environments. We are less concerned with formal peer-to-peer or blockchain dogmas and far more focused on practical, robust edge synchronization: building systems that can discover local nodes, store-and-forward critical data across ad-hoc transports (such as Wi-Fi and Bluetooth), and reconcile state once connectivity is restored.

This is real-world edge work built for dynamic field settings, rather than sterile cloud data centers or closed SCIF environments. You will architect software running across a hybrid footprint of edge nodes, mobile endpoints, and cloud sync services.

Responsibilities

Architect Resilient Transport & Sync Layers: Design and implement store-and-forward transport and data-synchronization protocols tailored for low-bandwidth, high-latency, and DDIL field conditions.

Ad-Hoc Networking & Discovery: Implement local peer discovery and async I/O transports operating over heterogeneous physical links, including Wi-Fi, Bluetooth/BLE, and ad-hoc mesh networks.

Field Ready Systems Engineering: Apply delay tolerant networking (DTN) principles and local conflict-free data synchronization (e.g., CRDTs and content-addressable storage) to ensure mission-critical applications function offline indefinitely.

Hybrid Edge & Mobile Integration: Develop and maintain software components spanning hybrid architectures bridging field edge devices, mobile environments, and upstream cloud services.

Performance & Resource Optimization: Lead tuning, memory management, and debugging for resource-constrained hardware operating in rugged, disconnected field deployments.

Security & Cryptographic Primitives: Understand and implement various authorization and authentication security patterns, suitable for DDIL and contested environments.

Cross Functional Collaboration: Partner with hardware, mobile, and backend teams to validate end-to-end functionality under simulated and live field constraints.

Qualifications

Core Requirements

5-7+ years of software engineering experience building robust systems software or distributed networking services.

Core Languages: Strong proficiency in Rust or other systems level languages (Go, C, or C++).

Resilient Networking Expertise: Demonstrated experience with store-and-forward architectures, delay-tolerant networks (DTN), async I/O, or local device-to-device transport layers (e.g., BLE, TCP/IP, socket-level async networking).

Edge & Offline First Mindset: Practical experience solving synchronization challenges under intermittent, contested, or low-throughput network constraints (DDIL).

Nice-to-Haves / Pluses

Experience with Android development (NDK, Kotlin, KMP, CMP, background sync services, or Bluetooth/Wi-Fi Direct stacks).

Familiarity with hybrid mobile/cloud application architecture and state reconciliation.

Hands-on experience testing and evaluating wireless networking hardware and software in physical field or operational testing environments (outside of traditional lab/SCIF environments).

Background in content-addressable data structures, Merkle DAGs, or CRDTs.