Senior Engineering Leader: Intelligent Edge & Firmware

BusPatrol; Austin (TX); On-site; USD 140,000 - 180,000; Full time

Benefits offered by this job

Lead innovation in edge AI and hardware

Collaborate with global leaders in AI/ML

Drive technologies that enhance safety

Job summary

BusPatrol in Austin, TX is looking for a Sr. Engineering Manager to drive the future of intelligent edge computing in firmware and hardware. This leadership role will oversee technology vision, guide high-performing teams, and ensure successful engineering execution for safety-critical decisions.

Ideal candidates should possess over 10 years of engineering experience, a strong background in embedded AI ecosystems, and a degree in engineering. This is a chance to influence product strategy and build a world-class engineering organization.

Qualifications

• 10+ years of engineering experience with significant expertise in embedded systems, firmware, hardware, or edge AI.
• 3+ years of engineering leadership in firmware engineering.
• Proven experience building and scaling multi-disciplinary engineering organizations.
• Expertise in embedded AI ecosystems and accelerators.

Responsibilities

• Define and drive technology vision and roadmap for intelligent edge computing.
• Build and mentor high-performing teams across embedded systems and edge AI.
• Ensure engineering programs meet strict performance, safety, and compliance requirements.
• Oversee architecture and design of embedded AI pipelines and firmware platforms.

Skills

Embedded systems

Firmware engineering

Edge AI

C/C++

Python

Yocto

Cross-compilation

Education

Bachelor’s or Master’s degree in Electrical Engineering, Computer Engineering, or related field

Tools

HailoRT

TensorRT

OpenVINO

TFLite

GStreamer

OpenCV

FFmpeg

Job description

BusPatrol in Austin, TX is looking for a Sr. Engineering Manager to drive the future of intelligent edge computing in firmware and hardware. This leadership role will oversee technology vision, guide high-performing teams, and ensure successful engineering execution for safety-critical decisions.

Ideal candidates should possess over 10 years of engineering experience, a strong background in embedded AI ecosystems, and a degree in engineering. This is a chance to influence product strategy and build a world-class engineering organization.