Embedded Signal Processing Engineer

Special Notice: This position is NOT contingent upon awarding of a project or needing a funding source. This is full-time employment with webAI. About Us: webAI is pioneering the future of artificial intelligence by establishing the first distributed AI infrastructure dedicated to personalized AI. We recognize the evolving demands of a data-driven society for scalability and flexibility, and 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 a company's 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. We are a team driven by truth, ownership, tenacity, and humility, and we seek individuals who resonate with these core values and are passionate about shaping the next generation of AI. About the Role: We are seeking an Embedded Signal Processing Engineer to support our Public Sector initiatives focused on building and optimizing production ready AI systems for secure and distributed environments. This role sits at the intersection of real-world tactical hardware, machine learning, signals processing, and multisensor engineering, translating them into autonomous field deployment. You will be responsible for deploying and prototyping AI models into embedded hardware systems for government edge environments in restricted and/or disconnected environments. Responsibilities: - Coordinate with AI and Network Software Engineers to design low-latency multi-node communication frameworks in restricted and/or disconnected environments. - Quantize, compile, and deploy real-time multi-agent pipelines for readiness across diverse edge architectures. - Develop algorithms for asynchronous multimodal data fusion, tracking, and signal processing. - Architect and maintain high-fidelity Hardware-in-the-Loop simulation environments to test autonomy algorithms. - Lead physical assembly, system calibration, and ruggedized field-testing of multi-node prototypes in unstructured environments. - Up to 25% travel to other webAI office locations, along with government field and test sites across the country What We Will Teach You: We understand that it is exceptionally rare to have AI experience on top of all of the responsibilities below. Therefore, we will be happy to train whoever we hire in AI to get up to speed on various aspects they will encounter including computer vision, edge AI systems and more. Qualifications: - 6+ years of professional experience in RF and networking architecture, tactical radio systems, physical bench-test simulation environments, and distributed middleware. - Hands-on experience with embedded systems, signal processing, and custom hardware integration. - Strong understanding of physical SWaP-C optimization, network partitioning, multi-stream ingestion and cross-platform development across systems like x86 and Jetson/ARM64. - Demonstrated expertise in C/C++ and Linux - Bachelor’s degree in a relevant field, or equivalent practical experience/military service. Advanced field experience is heavily preferred. Preferred Skills: - Experience developing, testing, or deploying autonomous software on tactical military or defense systems and open architecture standards. - Proven experience conducting field validation, site calibration, or operational testing of edge networks and ruggedized hardware in civilian commercial or tactical defense environments. We at webAI are committed to living out the core values we have put in place as the foundation on which we operate as a team. We seek individuals who exemplify the following: - Truth - Emphasizing transparency…