Autonomous Vehicle C++ Architect (Control-by-Wire)

Tensor Auto; San Jose (CA); On-site; USD 180,000 - 300,000; Full time

Job summary

Tensor is seeking a talented software engineer to design, implement, and maintain the control-by-wire module for multiple vehicle platforms. You will contribute to the architecture, debugging, and verification efforts for an advanced autonomous driving stack.

The role requires strong C++ skills, algorithms knowledge, and experience with middleware (gRPC/DDS/ROS). Join a team shaping the future of autonomous automotive technology and personal AGI-enabled mobility.

Qualifications

• Bachelor/Master degree in computer-related majors; 3+ years of work experience.
• Proficient in C++, familiar with C++11/14+ and strong debugging skills.
• Proficient in algorithms and data structures.
• Knowledge of architecture design, system analysis, software engineering.
• Proficient in at least one middleware (gRPC/DDS/ROS) with hands-on experience.
• Candidates with AEB, FCW, and KLA development experience preferred.

Responsibilities

• Software architecture design, development and maintenance of the control-by-wire module.
• Adaptation and tuning of the control-by-wire module on multiple vehicle platforms.
• Debugging and verification of the control-by-wire module, and writing test cases.
• Writing software design documents, participating in demand analysis and discussions.

Skills

C++

Algorithms

Data structures

Software architecture

Middleware (gRPC/DDS/ROS)

AEB/FCW/KLA experience

Education

Bachelor/Master in computer-related majors

Tools

gRPC

DDS

ROS

Job description

Tensor is seeking a talented software engineer to design, implement, and maintain the control-by-wire module for multiple vehicle platforms. You will contribute to the architecture, debugging, and verification efforts for an advanced autonomous driving stack.

The role requires strong C++ skills, algorithms knowledge, and experience with middleware (gRPC/DDS/ROS). Join a team shaping the future of autonomous automotive technology and personal AGI-enabled mobility.