Senior Edge AI Engineer - C++ & Vision Systems

Kargo; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Kargo is seeking a Senior Software Engineer to join our team in San Francisco, building high-performance C++ systems for edge devices and AI-driven perception on-vehicle. You will contribute to scalable software for distributed edge infrastructure and work across hardware and software to enable real-time logistics solutions.

You will mentor junior engineers, collaborate with engineering and product teams, and help optimize system performance, reliability, and scalability in real-world

Qualifications

• 5+ years of software engineering experience.
• Strong proficiency in C++ and modern development practices.
• Experience building production systems on Linux and distributed software.

Responsibilities

• Build high-performance C++ systems for machine vision and AI on edge devices.
• Develop advanced perception systems using 3D computer vision.
• Build agentic AI systems to deploy, manage, and monitor a growing fleet of edge devices.
• Design and implement scalable software for distributed edge infrastructure and device management.
• Optimize system performance, reliability, and scalability across hardware and software.
• Collaborate cross-functionally with engineering and product teams to deliver production-ready solutions.
• Mentor junior engineers through code reviews, technical guidance, and engineering best practices.

Skills

C++

Distributed systems

Edge computing

Machine learning

Linux

Performance optimization

Debugging

Education

Bachelor's/Master's in CS/CE/EE/Robotics

Tools

Linux

Job description

Kargo is seeking a Senior Software Engineer to join our team in San Francisco, building high-performance C++ systems for edge devices and AI-driven perception on-vehicle. You will contribute to scalable software for distributed edge infrastructure and work across hardware and software to enable real-time logistics solutions.

You will mentor junior engineers, collaborate with engineering and product teams, and help optimize system performance, reliability, and scalability in real-world