Embedded AI Architect (W2 Only)

Job Title: Architect / Technical Lead – Embedded AI Systems (In-Cab AI Assistant)

Location: Peoria, IL (Onsite)

Experience: 8+ Years

Must-Have Skills

• System Architecture & Technical Leadership
• Embedded Linux
• C/C++ and Python
• Embedded/Edge Computing Systems
• Hardware & Software Integration
• CAN, J1939, CDL or similar machine communication protocols
• AI/RAG (Grounded AI Assistant) knowledge
• OTA Updates, Diagnostics, Logging & Telemetry
• NVIDIA Orin/Jetson (Preferred)
• Voice Systems (ASR/TTS)
• Industrial/Automotive/Heavy Equipment domain

Job Summary

We are looking for an experienced Architect / Technical Lead to lead the end-to-end architecture of an AI-powered In-Cab Assistant platform for heavy equipment. The ideal candidate will have strong expertise in embedded Linux, system architecture, AI-enabled edge devices, hardware/software integration, and connected embedded systems. This role involves defining technical architecture, leading cross-functional engineering teams, ensuring safety and compliance, and driving integration of AI, voice, display, and machine interfaces.

Required Skills

• Bachelor''''s degree in Computer Engineering, Computer Science, Electrical Engineering, Software Engineering, or related field.
• 8+ years of experience in embedded software, systems engineering, or technical architecture.
• Strong experience with Embedded Linux and system-level software architecture.
• Proficiency in C/C++ and Python.
• Experience with embedded/edge AI platforms.
• Experience integrating compute, display, audio, and hardware components.
• Knowledge of CAN/J1939/CDL or similar industrial communication protocols.
• Experience with OTA updates, diagnostics, telemetry, logging, and device management.
• Familiarity with AI/RAG (Grounded AI Assistant) systems.
• Strong documentation, communication, and technical leadership skills.

Preferred Skills

• NVIDIA Orin/Jetson platform experience.
• Voice technologies (ASR, TTS).
• HMI development for industrial or automotive systems.
• Heavy equipment, automotive, robotics, or Industrial IoT experience.
• GPU programming.
• Cybersecurity architecture for connected embedded systems.
• Aftermarket or retrofit product development.
• Experience grounding AI using manuals, service documents, or fault data.